CN103501193A - Method for compensating for MU-MAS and dynamically adapting to MU-MAS - Google Patents
Method for compensating for MU-MAS and dynamically adapting to MU-MAS Download PDFInfo
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- CN103501193A CN103501193A CN201310407419.4A CN201310407419A CN103501193A CN 103501193 A CN103501193 A CN 103501193A CN 201310407419 A CN201310407419 A CN 201310407419A CN 103501193 A CN103501193 A CN 103501193A
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- H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
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- H04—ELECTRIC COMMUNICATION TECHNIQUE
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- H04B7/00—Radio transmission systems, i.e. using radiation field
- H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
- H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
- H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
- H04B7/0613—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission
- H04B7/0615—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal
- H04B7/0619—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal using feedback from receiving side
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- H04B7/0632—Channel quality parameters, e.g. channel quality indicator [CQI]
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- H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
- H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
- H04B7/0613—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission
- H04B7/0684—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission using different training sequences per antenna
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- H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
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- H04B7/0837—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station using pre-detection combining
- H04B7/0842—Weighted combining
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- H04J11/0023—Interference mitigation or co-ordination
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- H04J11/003—Interference mitigation or co-ordination of multi-user interference at the transmitter
- H04J11/0033—Interference mitigation or co-ordination of multi-user interference at the transmitter by pre-cancellation of known interference, e.g. using a matched filter, dirty paper coder or Thomlinson-Harashima precoder
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- H04L25/0224—Channel estimation using sounding signals
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- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L25/00—Baseband systems
- H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
- H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
- H04L25/03006—Arrangements for removing intersymbol interference
- H04L25/03343—Arrangements at the transmitter end
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Abstract
A method for compensating for MU-MAS and dynamically adapting to MU-MAS is described. The method for compensating for the MU-MAS comprises: transmitting a training signal from each antenna of a base station to one or each of a plurality of wireless client devices, one or each of the client devices analyzing each training signal to generate frequency offset compensation data, and receiving the frequency offset compensation data at the base station; computing MU-MAS precoder weights based on the frequency offset compensation data to pre-cancel the frequency offset at the transmitter; transmitting the training signal and analyzing the training signal on a link between each antenna and one or each of the plurality of wireless client devices to obtain channel characterization data at the base station; and receiving the channel characterization data at the base station; computing a plurality of MU-MAS precoder weights based on the channel characterization data to pre-cancel frequency and phase offset and/or inter-user interference; precoding data using the MU-MAS precoder weights to generate precoded data signals; and transmitting the precoded data signals through the antenna to the each respective client device.
Description
The application be that on 08 20th, 2008, application number are 200880102933.4 the applying date, name is called the dividing an application of application for a patent for invention of " system and method for distributed input distributed output wireless communications ".
Priority request
The application is the application NO.10/902 submitted to July 30 in 2004,978 continuation application.
Technical field
The present invention relates generally to field of wireless communications.Especially, the present invention relates to the system and method for the radio communication of the distributed input distributed output for using the space-time code technology.
Background technology
The space-time code of signal of communication
Space multiplex (MUX) and space-time code are newer development known in wireless technology.Owing to there being several antennas to be used in each terminal, so a kind of space-time code of specific type is called as " multi-input multi output " (MIMO).By with a plurality of antennas, carrying out sending and receiving, a plurality of independently radio waves can transmit in identical frequency range simultaneously.Following article provides the general introduction of MIMO.
IEEE member David Gesbert, IEEE member Mansoor Shafi, IEEE member Da-shan Shiu,, IEEE member Peter J.Smith and the senior member Ayman of IEEE Naguib IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL.21, NO.3, APRIL2003: " From theory to Practice:An Overview of MIMO Space-Time Coded Wireless Systems ".
The IEEE TRANSCTIONS ON COMMUNICATIONS of IEEE member David Gesbert, IEEE member Helmut Bolcskei, Dhananijay A.Gore and IEEE member Arogyaswami J.Paulraj, VOL.50, NO.12, DECEMBER2000: " Outdoor MIMO Wireless Channels:Models and Performance Prediction ".
Basically, the MIMO technology is based on for produce the application of the spatially distributed antenna of spatial data arranged side by side in common band.Radio wave is propagated by this way, thereby can separate and the demodulation individual signals at receiver, even they transmit in identical frequency band, this can cause the communication channel of independent on a plurality of statistical significances (namely effectively separating).Therefore, with the standard wireless communication system of making great efforts the inhibition multipath signal, compare (, a plurality of delay time signals of same frequency, and amplitude and phase place exist to be revised), MIMO can depend on irrelevant or weak relevant multipath signal, realizes higher throughput and the signal to noise ratio of improvement in given frequency band.Example shows, at power, under the condition suitable with signal to noise ratio (SNR), the MIMO technology has realized higher throughput (throughput), and traditional non-mimo system only can be realized lower throughput.Qualcomm's (high pass is maximum wireless technology supplier) website
http:// www.cdmatech.com/products/what_mimo_delivers.jsp:subscript is entitled as on the page of " What MIMO Delivers " has described this function: " MIMO is the only multiple antenna technique that increases spectral capacity by delivering two or more times the peak data rate of a system per channel or per MHz of spectrum.To be more specific, for wireless LAN or
applications QUALCOMM ' s fourth generation MIMO technology delivers speeds of315Mbps in36MHz of spectrum or8.8Mbps/MHz.Compare this to the peak capacity of802.11a/g (even with beam-forming or diversity techniques) which delivers only54Mbps in17MHz of spectrum or3.18Mbps/MHz ".
Usually upper, due to several reasons, mimo system is less than the actual property restriction (so the improvement in network is less than 10 * throughput) of 10 antennas facing to each device:
1. physical restriction: must there is enough intervals between the MIMO antenna on setter, thus each receiving and counting signal independently.Even, although still can see the improvement of MIMO throughput when the antenna spacing of wavelength mark, when antenna approaches more, efficiency worsens rapidly, this has caused lower MIMO throughput multiplication device.
Referring to for example below with reference to document:
[1]D.-S.Shiu,G.J.Foschini,M.J.Gans,and J.M.Kahn,“Fading correlation and its effect on the eapacity of multielement antenna systems,”IEEE Trans.Comm.,vol.48,no.3,pp.502-513,Mar.2000.
[2]V.Pohl,V.Jungnickel,T.Haustein,and C.von Helmolt,“Antenna spacing in MIMO indoor ehannels,”Proc.IEEE Veh.Technol.Conf.,vol.2,pp.749-753,May2002.
[3]M.Stoytchev,H.Safar,A.L.Moustakas,and S.Simon,“Compact antenna arrays for MIMO applications,”Proc.IEEE Antennas and Prop.Symp.,vol.3,pp.708-711,July2001.
[4]A.Forenza and R.W.Heath Jr.,“Impact of antenna geometry on MIMO communication in indoor clustered channels,”Proc.IEEE Antennas and Prop.Symp.,vol.2,pp.1700-1703,June2004.
In addition, for little antenna spacing, coupling effect each other may reduce the performance of mimo system.
Referring to for example below with reference to document:
[5]M.J.Fakhereddin and K.R.Dandekar,“Combined effect of polarization diversity and mutual coupling on MIMO capacity,”Proc.IEEE Antennas and Prop.Symp.,vol.2,pp.495-498,June2003.
[7]P.N.Fletcher,M.Dean,and A.R.Nix,“Mutual coupling in multi-element array antennas and its influence on MIMO channel capacity,”IEEE Electronics Letters,vol.39,pp.342-344,Feb.2003.
[8]V.Jungnickel,V.Pohl,and C.Von Helmolt,“Capaeity of MIMO systems with closely spaced antennas,”IEEE Comm.Lett.,vol.7,pp.361-363,Aug.2003.
[10]J.W.Wallace and M.A.Jensen,“Termination-dependent diversity performance of coupled antennas:Network theory analysis,”IEEE Trans.Antennas Propagat.,vol.52,pp.98-105,Jan.2004.
[13]C.Waldschmidt,S.Schulteis,and W.Wiesbeck,“Complete RF system model for analysis of compact MIMO arrays,”IEEE Trans.on Veh.Technol.,vol.53,pp.579-586,May2004.
[14]M.L.Morris and M.A.Jensen,“Network model for MIMO systems with coupled antennas and noisy amplifiers,”IEEE Trans.Antennas Propagat.,vol.53,pp.545-552,Jan.2005.
And crowded to together the time when antenna, antenna must be done littlely usually, this also can affect antenna efficiency.
Referring to for example below with reference to document:
[15]H.A.Wheeler,“Small antennas,”IEEE Trans.Antennas Propagat.,vol.AP-23,n.4,pp.462-469,July1975.
[16]J.S.McLean,“Are-examination of the fundamental limits on the radiation Q of electrically small antennas,”IEEE Trans.Antennas Propagat.,vol.44,n.5,pp.672-676,May1996.
Finally, with lower frequency and longer wavelength, the physical size of MIMO device just becomes and is difficult to process.An extreme example is at the HF wave band, and MIMO device antenna must 10 meters or larger distance separated from each other here.
2. noise limit.The receiver of each MIMO/transmitter subsystem produces the noise of certain level.When increasing this subsystem closes on mutually placement, background noise will rise.Simultaneously, when needs identify more unlike signals from multiple-antenna MIMO system, just require lower background noise.
3. cost and Power Limitation.Although in some MIMO application, cost and power consumption are not focuses, in typical wireless product, while developing a kind of successful product, cost and power consumption are all vital restraining factors.For each MIMO antenna, the RF subsystem need separated, comprise the mould of separation-number (A/D) and number-Mo (D/A) transducer.Unlike a lot of aspects of the digital system of weighing scale with Moore's Law (observed result of the experience aspect that cofounder Gordon mole of Intel has done, the transistor size on the integrated circuit of microdevice approximately just can quadruple every 24 months; Source: http://www.intel.com/technology/mooreslaw/), intensive like this analog subsystem has certain physical structure size and power requirement usually, and its size and cost and power linear are proportional.Therefore, with single antenna devices, compare, many antennas MIMO device will become extremely expensive and have surprising energy consumption.
As top result, most of mimo systems of today expection are on the grade of 2 to 4 antennas, cause the rising of 2 to 4 times of throughputs and the rising of some SNR (signal to noise ratio) of causing due to the diversity benefit of multiaerial system.Anticipated the mimo system (particularly due to shorter wavelength and nearer antenna spacing on higher microwave frequency) of 10 antennas, but, except special for some and to the insensitive application of cost, it is very unpractiaca surpassing 10 antennas.
Virtual antenna array
A kind of special applications of the technology of MIMO type is virtual antenna array.Advised this system in the research file that Euroscience technical field research cooperation tissue proposes; EURO; Barcelona; Spain; 15-17 day in January, 2003: Center for Telecommunication Research; King's College London, UK: " A step towards MIMO:Virtual Antenna Arrays ", Mischa Dohler & Hamid Aghvami.
Described in file, virtual antenna array is cooperation wireless device system (for example cell phone), its communication mutually on the communication channel of separating (mutually enough closing on if work as them), rather than at them on main communication channel with their base station communication, (for example make the work of collaborative ground, if they are the GSM cell phones in the UHF wave band, this can be the wireless wave band of industrial scientific medical (ISM) of 5GHz so).By forwarding information between the several devices in the relaying scope mutual (except in the scope of base station), just look like they be that to have physically a device job of a plurality of antennas the same, make single antenna devices realize potentially the throughput hoisting as the MIMO.
Yet in fact, the extremely difficult realization of such system and use are limited.At first, the rarest two different communication paths are to realize the throughput lifting now must to keep each device, and the availability of its second repeated link is often uncertain.And, there is the second communication subsystem because they are minimum and larger computation requirement is arranged, so this device being more expensive, physical size is larger, and consumes more power.In addition, by a plurality of communication links, this system depends on very complicated systematic live collaboration potentially.Finally, for example, because simultaneous channel usage (increases, use the simultaneous call transmission of MIMO technology), computation burden for each device has also just increased (the linearity increase with the channel utilization forms exponent increase usually), and this is very unpractiaca to the portable unit with strict power and size restrictions.
Summary of the invention
A kind of frequency for the multiaerial system (MAS) to having multi-user (MU) transmission (" MU-MAS ") and the system and method that phase deviation compensates have been described.For example, according to the method for one embodiment of the present invention, comprise: will be sent to from the training signal of each antenna of base station one or each wireless client device in a plurality of wireless client device, in this customer set up one or each customer set up are analyzed each training signal with the generated frequency bias compensation data, and in place, base station receive frequency bias compensation data; Calculate MU-MAS precoder weight to eliminate in advance the frequency shift (FS) at transmitter place based on described frequency offset compensation data; Use described MU-MAS precoder weight to carry out precoding to training signal, to generate the precoding training signal for each antenna of base station; To send to each wireless client device in described a plurality of wireless client device from the training signal after the precoding of each antenna of described base station, each customer set up is analyzed each training signal to generate the channel characteristics data, and receives described channel characteristics data in described base station; Calculate a plurality of MU-MAS precoding weights based on these channel characteristics data, this MU-MAS precoder weight is calculated the interference of eliminating between frequency and phase deviation and/or user for pre-; By MU-MAS precoder weight, data are carried out to precoding, to generate for the data-signal after the precoding of each antenna of base station; And each antenna by base station is sent to its each client device by the pre-code data signal after described precoding.
The accompanying drawing explanation
By reference to the accompanying drawings, below detailed description can obtain the present invention is better understood, wherein:
Fig. 1 has shown the mimo system of prior art.
Fig. 2 has shown the N antenna base station communicated with a plurality of single antenna customer set ups.
Fig. 3 has shown the base station of three antennas that communicate with three single antenna customer set ups.
Fig. 4 has shown the training signal technology of using in one embodiment of the present of invention.
Fig. 5 has shown and has been transferred to according to an embodiment of the invention the channel characteristics data of base station from customer set up.
Fig. 6 has shown the distributed output of multiple according to an embodiment of the invention input (" MIDO ") downlink transfer.
Fig. 7 has shown multi-input multi output (" MIMO ") uplink according to an embodiment of the invention.
Fig. 8 has shown the base station of circulating to distribute throughput by different customers according to an embodiment of the invention.
Fig. 9 has shown the client's grouping based on closing on according to an embodiment of the invention.
Figure 10 has shown the embodiments of the invention that use in the NVIS system.
Figure 11 has shown the execution mode of the DIDO transmitter with I/Q compensate function unit.
Figure 12 has shown the DIDO receiver with I/Q compensate function unit.
Figure 13 has shown a kind of execution mode of the DIDO-OFDM system with I/Q compensation.
Figure 14 has shown in the situation that have and do not have a kind of execution mode of I/Q compensation DIDO2 * 2 performances (performance).
Figure 15 has shown in the situation that have and do not have a kind of execution mode of I/Q compensation DIDO2 * 2 performances.
Figure 16 has shown in the situation that have and do not have a kind of execution mode of I/Q compensation for the SER (symbol error rate) of different Q AM planisphere.
Figure 17 has shown in the situation that the different user devices position has and do not have a kind of execution mode of I/Q compensation DIDO2 * 2 performances.
Figure 18 has shown in the situation that have and do not have a kind of execution mode of I/Q compensation SER in desirable (i.i.d. (independent and same the distribution)) channel.
Figure 19 has shown a kind of execution mode of the transmitter architecture of self adaptation DIDO system.
Figure 20 has shown a kind of execution mode of the receiver architecture of self adaptation DIDO system.
Figure 21 has shown a kind of execution mode of the method for self adaptation DIDO-OFDM.
Figure 22 has shown a kind of execution mode of the antenna arrangement of measuring for DIDO.
Figure 23 has shown the execution mode for the array configurations of different stage (order) DIDO system.
Figure 24 has shown the performance of different stage DIDO system.
Figure 25 has shown a kind of execution mode of the aerial array of measuring for DIDO.
Figure 26 has shown a kind of execution mode of the functional relation of the DIDO2 that 4-QAM and 1/2FEC lead * 2 performances and location of user equipment.
Figure 27 has shown a kind of execution mode of the antenna arrangement of measuring for DIDO.
Figure 28 has shown how DIDO8 * 8 produce the SE larger than the DIDO2 with low TX power demand * 2 in one embodiment.
Figure 29 has shown at a kind of execution mode with DIDO2 in day line options situation * 2 performances.
Figure 30 has shown average BER (BER) performance of different DIDO pre-coding schemes in the i.i.d. channel.
Figure 31 has shown the functional relation between the quantity of extra transmitting antenna in the snr gain of ASel and i.i.d. channel.
Figure 32 has shown in the situation that have 1 and 2 exterior antenna SNR threshold value in the i.i.d. channel and for the functional relation between the number of users (M) of block diagonalization (BD) and ASel.
Figure 33 has shown for being positioned at the equal angular direction and having two users' of different angles expansion (AS) value BER and every user's average SNR.
Figure 34 has shown the result similar with Figure 33, but has higher angle intervals between the user.
Figure 35 has drawn the different value for user's average arrival angle (AOA), the functional relation between AS and SNR threshold value.
Figure 36 has shown the SNR threshold value for 5 users' exemplary cases.
Figure 37, for 2 users' situation, provides in the situation that have 1 and 2 additional antenna, the comparison of SNR threshold value BD and ASel.
Figure 38 has shown the result similar with Figure 37, but for 5 users' situation.
Figure 39 has shown the SNR threshold value for the BD scheme with different AS values.
Figure 40 shown for the BD with 1 and 2 additional antenna and ASel, the SNR threshold value in having the space correlation channel of AS=0.1 °.
Figure 41 has shown the calculating for the SNR threshold value of two other channel conditions of AS=5 °.
Figure 42 has shown the calculating for the SNR threshold value of two other channel conditions of AS=10 °.
Figure 43-Figure 44 has shown respectively in the situation that 1 and 2 additional antenna, the functional relation between the angle spread (AS) of SNR threshold value and number of users (M) and BD and ASel scheme.
Figure 45 has shown the receiver that is equipped with frequency offset estimator/compensator;
Figure 46 has shown DIDO2 according to one embodiment of the present invention * 2 system models.
Figure 47 has shown the method according to one embodiment of the present invention.
Figure 48 has shown in the situation that have and do not have frequency shift (FS), the SER result of DIDO2 * 2 systems.
Figure 49 compares the SNR threshold performance of different DIDO schemes.
By the distinct methods execution mode, required amount of overhead compares Figure 50.
Figure 51 has shown at f
maxthe small frequency of=2Hz skew and there is no the emulation in the situation of integer offset correction.
Figure 52 has shown the result when closing the integer offset estimator.
Embodiment
In the following description, for the purpose of explaining, in order providing, the present invention to be understood thoroughly, to have illustrated a plurality of specific details.Yet, it is apparent that, for the one of ordinary skilled in the art, even without some specific details, still can realize the present invention.In addition, known construction and device is shown as the block diagram form, to avoid ultimata obfuscation of the present invention.
Fig. 1 has shown the prior art mimo system with transmitting antenna 104 and reception antenna 105.The throughput of such system can be realized 3 times of the common throughput of realizing in available channel.Have multiple diverse ways to realize the details of this mimo system, it had description in the publication document about this theme, and following explanation will be described such method.
Before data are transmitted in the mimo system of Fig. 1, channel is by " characterization ".This is by realizing starting that " training signal " is transferred to each receiver 105 from each transmitting antenna 104.Training signal has coding and mod subsystem 102 to generate, and is converted to analog signal by the D/A converter (not shown), then by each transmitter 103, from baseband signal, is converted to the RF signal.Each reception antenna 105 that is coupled to its RF receiver 106 receives each training signal and is converted into baseband signal.Baseband signal is converted to digital signal by the D/A converter (not shown), then this training signal of signal processing subsystem 107 characterizations.The feature of each signal can comprise several factors, and for example, it comprises, with respect to phase place and amplitude, absolute reference signal, relative reference signal, feature noise or other factors of the reference signal of receiver inside.The feature of each signal is normally defined the phase place of the performance several aspects of signal when signal transmits by channel and the vector of amplitude variations.For example, in the modulation signal of quadrature amplitude modulation (" QAM "), described feature may be the phase place of several multipaths reflection of signal and the vector of amplitude excursion.The another one example is that, in the signal of OFDM (" OFDM ") modulation, it may be several in the OFDM frequency spectrum or the phase place of all single component signals (sub-signal) and the vector of amplitude excursion.
The channel characteristics that signal processing subsystem 107 will be received by each reception antenna 105 and corresponding receiver 106 stores.After three all transmitting antennas 104 complete their training signal transmission, signal processing subsystem 107 will have been stored three for each channel characteristics in three reception antennas 105, this has formed 3 * 3 matrix 108, and it is expressed as channel characteristics matrix " H ".The matrix element H that each is independent
i, jit is the channel characteristics of the training signal transmission of the transmit antenna 104i that receives of reception antenna 105j.
In this, signal processing subsystem 107 inverts to produce H by matrix H 108
-1, and wait for from the transmission of the real data of transmitting antenna 104.Note, the multiple existing MIMO technology of describing in available document can be used for guaranteeing that H matrix 108 is reversible.
The content of the data that transmit in force, (payload) is delivered to data input subsystem 100.Then before delivering to coding and mod subsystem 102, it is assigned with device (splitter) 101 and is divided into three parts.For example, if content is the ASCII bit of " abcdef ", it just can be assigned with device and be divided into three sub-contents " ad ", " be " and " cf ".Then, every sub-content sends to separately coding and mod subsystem 102.
By using the statistical independence that is applicable to each signal and the coded system of error correcting capability, individually every sub-content encoded.These comprise, and are not limited only to, Reed-Solomon coding, Viterbi coding (Viterbi coding) and strengthen encode (Turbo Codes).Finally, each in the sub-content after using the modulator approach suitable to channel to these three codings is modulated.Exemplary modulator approach is differential phase keying (DPSK) modulation (" DPSK "), 64-QAM modulation and OFDM.Here it should be noted, the diversity gain that MIMO provides allows the modulation constellation of higher plate number, and described modulation constellation is also feasible in SISO (single-input single-output) system of using same channel.Then, the signal after each coding and modulation transfers out by its antenna 104, after the D/A conversion that described transmission is followed at D/A converting unit (not shown) and the RF of each transmitter 103 generate.
Suppose to have enough space diversitys to be present between the sending and receiving antenna, each reception antenna 105 will receive from antenna 104 various combination of three signal transmissions.Each RF receiver 106 receives and converts them to baseband signal by each signal, and then the A/D converter (not shown) carries out digitlization to signal again.If y
nthe signal received by n reception antenna 105, x
nbe the signal sent by n transmitting antenna 104, N is noise, and this just can describe with following equation so.
y
1=x
1H
11+x
2H
12+x
3H
13+N
y
2=x
1H
12+x
2H
22+x
3H
23+N
y
3=x
1H
13+x
2H
32+x
3H
33+N
Suppose that this is a system with three equatioies of three unknown quantitys, Here it is so, and signal processing subsystem 107 is derived x
1, x
2and x
3linear algebra problem (suppose that N is in enough low level, allow signal is decoded):
x
1=y
1H
-1 11+y
2H
-1 12+y
3H
-1 13
x
2=y
1H
-1 21+y
2H
-1 22+y
3H
-1 23
x
3=y
1H
-1 31+y
2H
-1 32+y
3H
-1 33
Once derive the signal x of three transmission
n, they are just by signal processing subsystem 107 demodulation, decoding and error correction, three bit streams that separate to recover former cause distributor 101.These bit streams merge in combiner unit 108, and are output as single data stream from data output 109.The supposing the system robustness can overcome noise induced damage, the bit streams that data output 109 produces so will be incorporated into data input 100 in bit stream the same.
Although described prior art systems is usually effectively until four antennas, perhaps until the antenna of 10 more than, owing to describing in the background parts of the disclosure, for example, while having a large amount of antennas (25,100 or 1000), it becomes very unactual.
Usually, such prior art systems is two-way, and return path realizes in identical mode, but conversely, in each side of communication channel, all has the sending and receiving subsystem.
Fig. 2 has shown one embodiment of the present of invention, and therein, base station (BS) 200 disposes wide area network (WAN) interface (for example connecting at a high speed by T1 or other) 201 and provide (N) antenna 202 of some.We use term " base station " to refer to any wireless site that carries out radio communication with one group of client of fixed position for the time being.The example of base station can be the access point in WLAN (wireless local area network) (WLAN), or WAN antenna or aerial array.Some customer set up 203-207 are arranged, and each has single antenna, and base station 200 is served them by wireless mode.Although the purpose for this example, be very easy to expect being positioned at the base station of office environment, in this environment, its user's set 203-207 that is the personal computer that is equipped with wireless network provides service, but this structure will apply to a large amount of applicable cases, indoor and outdoors, here wireless client is served in base station.For example, described base station can be positioned on cellular tower, or is positioned on television broadcast towers.In one embodiment, base station 200 is placed in ground, (for example frequency of 24MHz) up transmission for the HF frequency, so that signal is returned from ionospheric reflection, as proposed on April 20th, 2004, sequence number is No.10/817,731, what when exercise question is SYSTEM AND METHOD FOR ENHANCING NEAR VERTICAL INCIDENTCE SKYWAVE (" NVIS ") COMMUNICATION USING SPACE-TIME CODING, pending application was described is the same, it is by dispensing the application agent, here as a reference.
Some details interrelated with base station 200 and illustrated customer set up are only the purposes for illustration, rather than cardinal principle according to the present invention is essential.For example, this base station can be connected in a plurality of dissimilar wide area networks via wan interface 201, and it comprises private wide area network, for example those wide area networks that send for digital video.Similarly, customer set up can be wireless data processing and/or the communicator of any kind, and it comprises, and not only is confined to cell phone, personal digital assistant (" PDA "), receiver and wireless camera.
In one embodiment, the n of a base station antenna 202 spatially separates, thus the relevant signal of each sending and receiving non-space, just look like described base station be that the transceiver of prior art MIMO is the same.Described in background technology, the experiment that antenna is placed with interval, λ/6 (i.e. 1/6 wavelength) is made, it has successfully realized the throughput hoisting from MIMO, but in general, these antenna for base station are more separated, the performance of system is just better, λ/2nd, gratifying minimum range.Certainly, cardinal principle of the present invention is not limited to any specific separation between antenna.
Note, single base station 200 can be positioned over far distance by its antenna well.For example, in the HF frequency spectrum, antenna can have 10 meters or farther (for example, mention NVIS realize in) in the above.If use 100 such antennas, the aerial array of this base station just can occupy the area of several square kilometres.
Except space diversity reception to communicate, in order to improve the effective throughput of system, one embodiment of the present of invention are by polarizations.Improving channel capacity by polarization is a kind of known technology, and it has been used a lot of years by satellite television providers.Use Polarization technique, can make a plurality of (for example three) base stations or user antenna very approaching with each other, and it is relevant to remain non-space.For example, although traditional RF system is mostly just benefited from two dimension (x and the y) diversity of polarization, structure described herein can further be benefited from three-dimensional (x, y and the z) diversity of polarization.
Except space and polarization diversity, one embodiment of the present invention adopt the antenna pattern (pattern) that is close to quadrature, via the directional diagram diversity, to improve link performance.The directional diagram diversity can be improved capacity and the bit error rate performance of mimo system, and its advantage than other diversity antenna technologies can be referring to following article:
[17]L.Dong,H.Ling,and R.W.Heath Jr.,“Multiple-input multiple-output
wireless communication systems using antenna pattern diversity,”Proc.IEEE Glob.Telecom.Conf.,vol.1,pp.997-1001,Nov.2002.
[18]R.Vaughan,“Switched parasitic elements for antenna diversity,”IEEE
Trans.Antennas Propagat.,vol.47,pp.399-405,Feb.1999.
[19]P.Mattheijssen,M.H.A.J.Herben,G.Dolmans,and L.Leyten,“Antenna-pattern diversity versus space diversity for use at handhelds,”IEEE Trans.on Veh.Technol.,vol.53,pp.1035-1042,July2004.
[20]C.B.Dietrich Jr,K.Dietze,J.R.Nealy,and W.L.Stutzman,“Spatial,polarization,and pattern diversity for wireless handheld terminals,”Proc.IEEE Antennas and Prop.Symp.,vol.49,pp.1271-1281,Sep.2001.
[21]A.Forenza and R.w.Heath,Jr.,“Benefit of Pattern Diversity Via2-element Array of Circular Patch Antennas in Indoor Clustered MIMO Channels”,IEEE Trans.on Communications,vol.54,no.5,pp.943-954,May2006.
By using the directional diagram diversity, can make a plurality of base stations or user antenna very approaching each other, and however also can spatially not be associated.
Fig. 3 provides the additional detail of the embodiment of the base station 200 shown in Fig. 2 and customer set up 203-207.For the purpose of simplifying, this base station 300 only is shown as three antennas 305 and three customer set up 306-308.Yet, it should be noted that embodiments of the invention described herein can with the antenna 305 of unlimited amount almost (that is, only by can with space and noise limit) and customer set up 306-308 realize.
Prior art MIMO structure shown in Fig. 3 and Fig. 1 is similar, and wherein, both have three antennas at each end of communication channel.Significant difference is, in the mimo system of prior art, between three antennas 105 on Fig. 1 right side are mutual, be fixed range (for example, being integrated in single device), the signal received from each antenna 105 is processed together signal processing subsystem 107.By contrast, in Fig. 3, three antennas on figure right side 309 each to be coupled to different customer set up 306-308 upper, each described customer set up can be distributed in the scope of base station 305 Anywhere.Like this, the signal that each customer set up receives can be encoded at it, be independent of other two signals that receive and processed in modulation, signal processing subsystem 311.Therefore, with " MIMO " system of the multiple output of multiple input (being antenna 105) (being antenna 104), compare, Fig. 3 has shown the distributed output of multiple input (being antenna 305) (being antenna 305) system, below refers to " MIDO " system.
Note, the application uses the term usage different from application before, to meet better academia and industrial practice.The application NO.10/817 of the common pending trial that is entitled as " SYSTEM AND METHOD FOR ENHANCING NEAR VERTICAL INCIDENCE SKYWAVE (" NVIS ") COMMUNICATION USING SPACE-TIME CODING " of submitting in 20 days April in 2004 quoting before, the application NO.10/902 that on July 30th, 731 and 2004 submits to, in 978 (the application is the continuation application of this application), the meaning of " input " and " output " (in environment of SIMO, MISO, DIMO and MIDO) and this term expressing the meaning in this application is contrary.In application before, " input " refers to input to the wireless signal of reception antenna (for example, the antenna 309 in Fig. 3), and " output " refers to the wireless signal of transmitting antenna (for example, antenna 305) output.In academia and wireless industry, usually use the antisense of " input " and " output ", the wireless signal that wherein " input " refers to input to channel (, the wireless signal sent from antenna 305), and " output " refers to from the wireless signal (that is the wireless signal that, antenna 309 receives) of channel output.The application adopts this term usage, and this usage is contrary with the usage in the application of quoting before this section.Therefore, below illustrated the term usage equivalent form of value between several applications:
MIDO structure shown in Fig. 3 has realized being similar to for the transmitting antenna of giving determined number the capacity lifting that MIMO realizes on the SISO system.Yet, the difference of specific MIDO embodiment shown in MIMO and Fig. 3 is, for realizing that the capacity that a plurality of antenna for base station provide promotes, each MIDO customer set up 306-308 only requires single receive antenna, and, for MIMO, each customer set up at least requires and wishes the as many reception antenna of capacity multiple of realizing.Suppose usually to have the restriction of an implementation, its restriction can be placed how many antennas (as explained in background technology) at customer set up, and on the typical case, this just is limited in mimo system between 4 to 10 antennas (capacity of 4 times to 10 times).Usually from fixing and fill dynamic location-based service in a lot of customer set ups, it is expanded to 10 antennas that surpass far away due to base station 300, and with suitable apart from separate antenna, with the implementation space diversity, be very actual.As described in, each antenna arrangement has the disposal ability of transceiver 304 and a part of coding, modulation and Signal Processing Element 303.It should be noted that, in this embodiment, no matter base station 300 expansions are how many, and each customer set up 306-308 will only require an antenna 309, therefore the cost for alone family customer set up 306-308 will be very low, and the cost of base station 300 can be shared in the user of large cardinal.
In Fig. 4 to Fig. 6, shown the example that how to complete 300 transmission of the MIDO to customer set up 306-308 from base station.
In one embodiment of the invention, before the MIDO transmission starts, channel is characterized.For mimo system, 405 pairs of training signals of each antenna are transmitted one by one.Fig. 4 has only shown the transmission of first training signal, but, for three antennas 405, has three transmission that separate.Each training signal is generated by coding, modulation and signal processing subsystem 403, converts analog signal to by D/A converter, and sends by each RF transceiver 404 as the RF signal.Available various coding, modulation and signal processing technology comprise, and be not limited to those above-described technology (for example, Reed Solomon, Viterbi coding (Viterbi Coding); QAM, DPSK, QPSK modulation etc.).
Each customer set up 406-408 receives training signal and converts this training signal to baseband signal by transceiver 410 by its antenna 409.The place that the A/D converter (not shown) is encoded at this signal, modulation and signal processing subsystem 411 processed converts thereof into digital signal.Then the feature (for example, identifying above-mentioned phase place and amplitude distortion) of signal characteristic logical block 320 identification gained signals also is stored in this feature in memory.This characteristic processing process is similar to the processing procedure of the mimo system of prior art, and a significant difference is that each customer set up only calculates an one antenna, rather than the characteristic vector of n antenna.For example, the described training signal of known mode is by the coding of customer set up 406, modulation and signal processing subsystem 420 initialization (when producing by the information sending, receiving it, or by other initialization process).When antenna 405 sends this training signal with known mode, coding, modulation and signal processing subsystem 420 use correlation methods find the strongest training signal receiving mode, it preserves phase place and amplitude excursion, and then it cuts this pattern in the middle of the signal received.Next, it finds second strong cohesiveness relevant to described training signal to receive pattern, and phase place and amplitude excursion are preserved, and then it cuts the second strong mode from the described signal received.This processing is carried out always, for example, until preserved the phase place of certain fixed qty and amplitude excursion (, 8) or detectable training signal pattern, drops under given background noise.The vector of this phase/amplitude skew becomes the element H of vector 413
11.Meanwhile, customer set up 407 and 408 coding, modulation and signal processing subsystem are carried out same processing, produce their vector element H
21and H
31.
The memory that channel characteristics is deposited can be nonvolatile memory, for example flash memory, or hard disk, and/or volatile memory, for example random access memory (for example, SDRAM, RDAM).In addition, different user's sets can be stored characteristic information (for example PDA is used flash memory, and notebook computer uses hard disk) with dissimilar memory simultaneously.On various customer set ups or base station, ultimata of the present invention is not limited to the storing mechanism of any particular type.
As mentioned above, according to used scheme, because each customer set up 406-408 only has an antenna, each only stores 1 * 3 row 413-415 of H matrix.Fig. 4 has shown the stage after the first training signal transmission, and here, the first row of 1 * 3 row 413-415 has been stored the channel characteristics information of first antenna of three antenna for base station 405.All the other two row have been stored from the channel characteristics of ensuing two training signals transmission of all the other two antenna for base station.Note, for the purpose of illustration, described three time tranfers that the training signal pattern is being separated.Thereby, if selected three training signal patterns uncorrelated mutually, they can transmit so simultaneously, therefore reduce the training time.
As shown in Figure 5, after all three pilot transmission complete, each customer set up 506-508 sends it back base station 500 by 1 * 3 row 513-515 of the matrix H that stored.For the purpose of simplifying, only show a customer set up 506 and transmit its characteristic information in Fig. 5.For example, in conjunction with suitable error correction coding (Reed Solomon, Viterbi coding (Viterbi Coding) and/or enhancing coding (Turbo Codes)), can use suitable modulator approach (for example DPSK, 64QAM, OFDM) to guarantee that base station 500 receives the data in row 513-515 exactly.
In Fig. 5, although all three antennas 505 demonstrate the reception signal, for the transmission that receives every 1 * 3 row 513-515, the single antenna of base station 500 and single transceiver are enough.Yet, under certain condition, receiving each transmission (that is, in coding, modulation and signal processing subsystem 503, using single input multiple output (" SIMO ") treatment technology of prior art) with a lot of or all antennas 505 and transceiver 504 can realize than single antenna 505 and transceiver 504 better signal to noise ratios (SNR).
When coding, modulation and the signal processing subsystem 503 of base station 500 receive described 1 * 3 row 513-515 from each customer set up 507-508, it deposits described 1 * 3 row 513-515 in 3 * 3 H matrix 516.For customer set up, storage matrix 516 can be carried out by a lot of different memory technologies in base station, and it includes, but are not limited to, nonvolatile mass storage (for example hard disk) and/or volatile memory (for example SDRAM).Fig. 5 has shown that base station has received and stored the stage from 1 * 3 row 513 of customer set up 509.When 1 * 3 row 514 and 515 transmits from all the other customer set ups, they can be transmitted and be kept in H matrix 516, until whole H matrix 516 is stored.
With reference to figure 6, the embodiment of 600 transmission of the MIDO to customer set up 606-608 from base station will be described now.Because each customer set up 606-608 independently installs, so each device receives different transfer of data.Like this, the embodiment of base station 600 comprises between wan interface 601 and coding, modulation and signal processing subsystem 603 they is communicated to the router 602 of contact, it receives a plurality of data flow (form is bit stream) from wan interface 601, correspond respectively to each customer set up 606-608 by described data flow by the data flow u separated
1-u
3send.For this purpose, this router 602 can be used various known route technologies.
As shown in Figure 6, by described three bit streams, u
1-u
3route is advanced in described coding, modulation and signal processing subsystem 603, they are encoded to and (for example add up independently error correction stream, use Reed Solomon, Viterbi or strengthen coding), and use the modulator approach suitable to channel (for example DPSK, 64QAM or OFDM) by they modulation.In addition, the embodiment that Fig. 6 shows comprises signal precoding logical block 630, and based on signal characteristic matrix 616, this signal precoding logical block 630 is carried out unique coding for the signal to sending from each antenna 605.Especially, in this embodiment, precoding logical block 630 is by three bit stream u in Fig. 6
1-u
3be multiplied by mutually and generate three new bit stream u ' with the inverse matrix of H matrix 616
1-u '
3, rather than each coding and the bit stream modulated are routed to antenna (as done in Fig. 1) separately.Then, the D/A converter (not shown) is changed to analog signal by described three precoding bit circulation, and transceiver 604 and antenna 605 send it as the RF signal.
Before explaining how customer set up 606-608 receives described special stream, will the operation of precoding module 630 execution be described.Be similar to the example of MIMO in top Fig. 1, in three original bit stream, the coding of each bit stream and the signal of modulating will be expressed as u
n.In the embodiment shown in fig. 6, each u
ithe data that three bit streams that comprise 602 routes of router come, each such bit stream will become three user's set 606-608 one of them.
Yet, do not resemble the MIMO example in Fig. 1, there, each x
ithere is each antenna 104 to send, in the embodiments of the invention shown in Fig. 6, at each customer set up antenna 609, receive each u
i(adding noise N any in upper signal channel).For realizing such result, (we are expressed as v by it in the output of each in three antennas 605
i) be u
ifunction with the H matrix of each customer set up of characterization.In an embodiment, the precoding logical block 630 in coding, modulation and signal processing subsystem is calculated each v by carrying out following equation
i:
v
1=u
1H
-1 11+u
2H
-1 12+u
3H
-1 13
v
2=u
1H
-1 21+u
2H
-1 22+u
3H
-1 23
v
3=u
1H
-1 31+u
2H
-1 32+u
3H
-1 33
Therefore, unlike MIMO, there, channel will calculate each x at receiver after the signal conversion
i, and embodiments of the invention described herein solved each v at transmitter before channel is by the signal conversion
i.Each antenna 609 receives u for other antenna 609 from other
n-1the u separated in bit stream
i.The signal that each transceiver 610 will respectively receive converts baseband signal to, and the A/D converter (not shown) carries out digitlization to it here, and each coding, modulation and signal processing subsystem 611 are to its x
ibit stream carries out the demodulation code, and its bit stream is delivered to the data-interface 612 (for example, the application program on customer set up) that customer set up is used.
Embodiments of the invention described herein can be realized with multiple different coding and modulator approach.For example, in OFDM realizes, its intermediate frequency spectrum is divided into a plurality of minutes frequency bands, and technology described herein can be used for each independent minute frequency band of characterization.Yet as mentioned above, cardinal principle of the present invention is not limited to any specific modulator approach.
If customer set up 606-608 is portable data processing device, for example PDA, notebook computer and/or wireless telephonic words, because customer set up may move to another one from a position, channel characteristics can frequently change so.Like this, in one embodiment of the invention, the channel characteristics matrix 616 of base station is constantly upgraded.In one embodiment, new training signal is sent to each customer set up in base station 600 (every 250 milliseconds) periodically, each customer set up by its channel characteristics vector constantly send it back base station 600 with guarantee channel characteristics keep accurately (for example, if thereby environment change or customer set up move have influence on channel).In one embodiment, in sending to the actual data signal of each customer set up, training signal is interweaved.Typically, the throughput of described training signal is far below the throughput of described data-signal, so the almost not impact of this throughput total on system.Correspondingly, in this embodiment, channel characteristics matrix 616 can constantly be upgraded while initiatively communicating with each customer set up in base station, thereby moves to next position from a position when customer set up, thereby or environment change when having influence on channel and keep channel characteristics accurately.
One embodiment of the present of invention shown in Fig. 7 are improved uplink communication channel (that is, from customer set up 706-708 to base station 700 channel) by the MIMO technology.In this embodiment, the uplink channel characteristics logical block in base station 741 is constantly analyzed and characterization the channel come from each customer set up.Especially, each customer set up 706-708 sends training signal to base station 700, and there channel characteristics logical block 741 analyzes to produce the channel characteristics matrix 741 of N * M, and N is the quantity of customer set up here, and M is the quantity of the antenna that uses of base station.Embodiment shown in Fig. 7 is used three antennas 705 and three customer set up 706-708 in base station, this has caused depositing in 3 * 3 channel characteristics matrixes 741 of base station 700.Customer set up can be by the MIMO uplink shown in Fig. 7 for sending it back data base station 700 and the channel characteristics vector sent back to base station 700, as shown in Figure 5.But different with the embodiment shown in Fig. 5 is, in Fig. 5, the channel characteristics vector of each customer set up was transmitted with the time of separating, and the method shown in Fig. 7 allows from a plurality of customer set ups the channel characteristics vector to be transmitted go back to base station 700 simultaneously, thereby greatly reduce the impact of channel characteristics vector on the Return Channel throughput.
As mentioned above, the feature of each signal can comprise several factors, and for example, it comprises phase place and amplitude with respect to the reference signal of receiver inside, absolute reference signal, relative reference signal, feature noise or other factors.For example, in the signal of modulating in quadrature amplitude modulation, described feature can be phase place and the amplitude excursion vector of several multipath reflections of signal.Another example is that, in the signal of modulating at OFDM, described feature can be phase place and the amplitude excursion vector of several in the OFDM frequency spectrum or all single component signals.Described training signal can be generated by coding and the mod subsystem 711 of each customer set up, and the D/A converter (not shown) converts this training signal to analog signal, and then the transmitter 709 of each customer set up converts it to RF signal from baseband signal.In one embodiment, synchronous in order to ensure training signal, customer set up only transmits training signal (for example,, in the situation that circulation (round robin)) in base station requests.In addition, can the actual data signal sent from each customer set up, to training signal, be interweaved, or training signal can transmit together with described actual data signal.Therefore, even customer set up 706-708 is mobile, uplink channel characteristics logical block 741 also can be transmitted continuously and analyze this training signal, thereby guarantees that channel characteristics matrix 741 keeps upgrading.
Total channel capacity that previous embodiment of the present invention is supported can be defined as min (N, M), and here, M is the quantity of customer set up, and N is the quantity of antenna for base station.That is to say, capacity is limited by the antenna amount of base station side or customer side.So, one embodiment of the present of invention guarantee to be no more than the individual antenna of min (N, M) within preset time in sending/receiving by simultaneous techniques.
In typical situation, the quantity of the antenna 705 of base station 700 will be less than the quantity of customer set up 706-708.Fig. 8 has shown an exemplary situation, and it allows 5 customer set up 804-808 and the base station with three antennas 802 to communicate.In this embodiment, determine the quantity of total customer set up 804-808 and (for example necessary channel characteristics information detected, top description) afterwards, first crowd of three client 810 that communicate with it (because min (N is selected in base station 800, M)=3, so be three clients in this example).After the fixed time of having communicated by letter with first crowd of client 810, three clients 811 that base station just selects another group to communicate with.For the uniform distribution communication channel, two customer set ups 807,808 in first group are selected not to be included in base station 800.In addition, because extra antenna is available, the extra customer set up 806 in first group is just selected to be included in base station 800.In one embodiment, circulating the client masses by this way in base station 800, thereby can effectively distribute to each client throughput of equal number in time.For example, for the uniform distribution throughput, any combination (that is, because customer set up 806 communicates with base station for two circulations starting) of three customer set ups except customer set up 806 can then be selected in base station.
In one embodiment, except the data communication of standard, base station can be transmitted training signal by aforementioned techniques and be received training signal and signal characteristic data to each customer set up with from each customer set up.
In one embodiment, some customer set up or customer set up group can be assigned to the throughput of varying level, for example, can distinguish order of priority to customer set up, thereby the client that the customer set up that can guarantee high priority relatively must lower priority fills family, more communication cycle (that is, more throughput) is arranged.Variable based on some, can be selected client " priority ", described variable comprises, for example, user's the subscription fee to wireless bandwidth (for example, for being willing to mean additional throughput, pay more), and/or communication to/for example, from data type (, the real time communication, such as call voice and video of customer set up, acquisition for example, higher than the priority of non-realtime traffic, Email).
In the present load required based on each customer set up, in the embodiment of base station dynamic assignment throughput.For example, if customer set up 804 live video streams, and other device 805-808 is carrying out for example non real-time function of Email, base station 800 distributes relatively many throughputs can to this client 804 so.Yet, it should be noted, cardinal principle of the present invention is not limited to any specific throughput distribution technology.
As shown in Figure 9, two customer set ups 907,908 can be very approaching, and the channel characteristics that makes described client is the same actually.As a result, base station will receive and store the in fact equal channel characteristics vector of two customer set ups 907,908, so this can not produce, signal spatial distribution unique for each client.Correspondingly, in one embodiment, base station will guarantee that any two or more customer set ups that the phase mutual edge distance approaches very much are assigned to different groups.For example, in Fig. 9, at first communicate by letter with customer set up 904,905 and 908 first group 910 base station 900, then with second group 911 of customer set up 905,906,907, communicates by letter, and this has guaranteed that customer set up 907 and 908 is in different groups.
Selectively, in one embodiment, 900 whiles of base station and customer set up 907 and 908 communicate, but to communication channel, carry out multiplexing with known multi-channel Technology.For example, base station can be used time division multiplexing (" TDM "), frequency division multiplexing (" FDM ") or code division multiple access (" CDMA ") technology to carry out separately single, signal space correlation between customer set up 907 and 908.
Although above-mentioned each customer set up is equipped with single antenna, the customer set up that can have a plurality of antennas by use realizes that cardinal principle of the present invention is to improve throughput.For example, in the time of on being used in above-mentioned wireless system, the client with 2 antennas will realize the throughput hoisting of 2 times, and the client with 3 antennas will realize the throughput hoisting of 3 times, etc. (that is, supposing that space and angular separation between antenna are enough).When the customer set up by having a plurality of antennas circulates, same general rule can be applied in base station.For example, it can regard each antenna as client separately, and gives that " client " by throughput distribution, just as it is any other client, (for example, guarantees that each client provides enough or suitable communication cycle).
As mentioned above, one embodiment of the present of invention are used above-mentioned MIDO and/or MIMO signal transmission technology to improve signal to noise ratio and throughput near vertical incident sky wave (" NVIS ").With reference to Figure 10, in one embodiment of the invention, be equipped with the NVIS base station 1001 of matrix of N antenna 1002 for communicating with M customer set up 1004.The antenna 1004 of described NVIS antenna 1002 and multiple user's set is approximately to become 15 degree with interior angle, signal uplink is transmitted to obtain the NVIS wanted and drops to minimum by the surface wave disturbing effect with vertical direction.In one embodiment, antenna 1002 and customer set up 1004 used assigned frequency in the NVIS frequency spectrum of above-mentioned multiple MIDO and MIMO technology (for example, in carrier frequency or lower than the frequency of 23MHz, but be usually less than on the frequency of 10MHz) support a plurality of independently data flow 1006, thereby significantly improved throughput in assigned frequency (that is, with add up the independently quantity of data flow be directly proportional).
The described NVIS antenna of serving given base station can have far physical distance each other.Suppose the long distance (the round distances of 300 miles) of propagating lower than long wavelength and the signal of 10MHz, the hundreds of code, or even the antenna physical separation of several miles can provide benefit on diversity.Under such condition, independent aerial signal can be withdrawn into center, by traditional wired or wireless communication system, it is processed.Selectively, each antenna can have local device and process its signal, then by traditional wired or wireless communication system, this transfer of data is gone back to center.In one embodiment of the invention, NVIS base station 1001 has the wideband link 1015 of to internet 1010 (or other wide area networks), thus offer customer set up 1003 long-range, at a high speed, wireless network access.
In one embodiment, base station and/or user can utilize polarization/direction figure diversity (pattern diversity) technology, with when diversity being provided and promoting throughput, reduce array size and/or user distance.For example, in the DIMO system with HF transmission, due to polarization/direction figure diversity, the user can be positioned at same position and their signal can not be associated.Especially, by using the directional diagram diversity, a user can communicate with base station via earthwave, and other users can communicate with base station via NVIS.
Additional execution mode of the present invention
I,
utilize the I/Q imbalance to carry out the DIDO-OFDM precoding
The system and method that one embodiment of the present invention adopt inphase quadrature (I/Q) imbalance for distributed input distributed output (DIDO) system to having OFDM (OFDM) to compensate.In brief, according to present embodiment, subscriber equipment estimated channel, and by this information feedback to base station; Base station calculates pre-coding matrix, to eliminate between the carrier wave that the I/Q imbalance caused and the interference between the user; And parallel data stream is sent to a plurality of subscriber equipmenies via the DIDO precoding; This subscriber equipment forces (ZF), least mean-square error (MMSE) or maximum likelihood (ML) receiver to carry out demodulation to data via zero, to suppress residual interference.
As detailed below, some notable features of this execution mode of the present invention include, but are not limited to:
Precoding with for eliminate ofdm system from mirror image adjust (mirror tone) inter-carrier interference (ICI) (because of I/Q do not mate caused);
Precoding with the inter-user interference for eliminating the DIDO-OFDM system and ICI (because of I/Q do not mate caused);
For the ZF receiver of the DIDO-OFDM system via adopting block diagonalization (BD) eliminate ICI (because of I/Q do not mate cause) technology;
For via the precoding (at the transmitter place) of DIDO-OFDM system and ZF or MMSE filter (at the receiver place), eliminate inter-user interference and ICI (because of I/Q do not mate cause) technology;
For via the precoding (at the transmitter place) of DIDO-OFDM system and the nonlinear detector (at the receiver place) that is similar to maximum likelihood (ML) detector, eliminate inter-user interference and ICI (because of I/Q do not mate cause) technology;
The precoding of use based on channel condition information with for eliminate the inter-carrier interference (ICI) that ofdm system adjusts from mirror image (because of I/Q do not mate caused);
The precoding of use based on channel condition information with for eliminate the inter-carrier interference (ICI) that the DIDO-OFDM system adjusts from mirror image (because of I/Q do not mate caused);
At the place, base station, use I/Q not mate known DIDO precoder (I/Q mismatch aware DIDO precoder), and use the known DIDO receiver of I/Q at the user terminal place;
At the place, base station, use I/Q not mate known DIDO precoder (I/Q mismatch aware DIDO precoder), use the known DIDO receiver of I/Q at the user terminal place, and use I/Q known channel estimator;
At the place, base station, use I/Q not mate known DIDO precoder, use the known DIDO receiver of I/Q at the user terminal place, and use I/Q known channel estimator and the known DIDO feedback of I/Q maker (this maker is sent to website by channel condition information from user terminal);
At the place, base station, use I/Q not mate known DIDO precoder, and the known DIDO configurator of use I/Q (this configurator is carried out various functions with the I/Q channel information, comprises user's selection, adaptive coding and modulation, the mapping of empty time-frequency or precoder selection);
Use the known DIDO receiver of I/Q (this receiver via the ZF receiver in the DIDO-OFDM system that adopts block diagonalization (BD) precoder eliminate ICI (because of I/Q do not mate cause));
Use the known DIDO receiver of I/Q (this receiver via the precoding in the DIDO-OFDM system (at the transmitter place) and the nonlinear detector (at the receiver place) that is similar to maximum likelihood (ML) detector eliminate inter-user interference and ICI (because of I/Q do not mate cause)); And
Use the known DIDO receiver of I/Q (this receiver via the ZF in the DIDO-OFDM system or MMSE filter eliminate ICI (because of I/Q do not mate cause)).
A,
background
The sending and receiving signal of exemplary radio communication system comprises inphase quadrature (I/Q) component.In actual system, this inphase quadrature component may the distortion due to the defect in mixing and baseband operations.These distortions (distortion) show as I/Q phase place, gain and delay and do not mate.Sine (sine) and cosine (cosine) the incorrect quadrature of unbalance in phase in modulator/demodulator causes.Gain is uneven to be caused by the different amplification between the inphase quadrature component., also may there be additional distortion in delay difference due between the I in analog circuit and Q track (rail), and this distortion is referred to as to postpone uneven.
In OFDM (OFDM) system, the intercarrier uneven (ICI) that the I/Q imbalance can cause coming spontaneous emission to be adjusted.This impact has obtained research in some data, and in following information, proposed not mate the method compensated: M.D.Benedetto and P.Mandarini for the I/Q to single-input single-output SISO-OFDM system, " Analysis of the effect of the I/Q baseband filter mismatch in an OFDM modem; " Wireless personal communications, pp.175-186,2000; S.Schuchert and R.Hasholzner, " A novel I/Q imbalance compensation scheme for the reception of OFDM signals, " IEEE Transaction on Consumer Electronics, Aug.2001; M.Valkama, M.Renfors and V.Koivunen, " Advanced methods for I/Q imbalance compensation in communication receivers, " IEEE Trans.Sig.Proc, Oct.2001; R.Rao and B.Daneshrad, " Analysis of I/Q mismatch and a cancellation scheme for OFDM systems, " IST Mobile Communication Summit, June2004; A.Tarighat, R.Bagheri and A.H.Sayed, " Compensation schemes and performance analysis of IQ imbalances in OFDM receivers, " Signal Processing, IEEE TransactiohS on[also can be referring to Acoustics, Speech, and Signal Processing, IEEE TransactiohS on], vol.53, pp.3257-3268, Aug.2005.
The expansion of this work to multiple-input and multiple-output MIMO-OFDM system has been shown: R.Rao and B.Daneshrad in following information, " I/Q mismatch cancellation for MIMO OFDM systems; " in Personal, Indoor and Mobile Radio CommunicatiohS, 2004; PIMRC2004.15th IEEE International Symposium on, vol.4,2004, pp.2710-2714.For spatial reuse (SM), refer to R.M.Rao, W.Zhu, S.Lang, C.Oberli, D.Browne, J.Bhatia, J.F.Frigon, J.Wang, P; Gupta, H.Lee, D.N.Liu, S.G. Wong, M.Fitz, B.Daneshrad, and O.Takeshita, " Multiantenna testbeds for research and education in wireless communications; " IEEE Communications Magazine, vol.42, no.12, pp.72-81, Dec.2004; S.Lang, M.R.Rao and B.Daneshrad, " Design and development of a5.25GHz software defined wireless OF DM communication platform; " IEEE Communications Magazine, vol.42, no.6, pp.6-12, June2004; For orthogonal space time packet (OSTBC), refer to A.Tarighat and A.H.Sayed, " MIMO OFDM receivers for systems with IQ imbalances; " IEEE Trans.Sig.Proc, vol.53, pp.3583-3596, Sep.2005.
Unfortunately, the data that does not exist at present introduction how the gain of the I/Q in distributed input distributed output (DIDO) communication system and unbalance in phase error to be proofreaied and correct.The embodiment of the present invention of the following stated provides a kind of scheme addressed these problems.
The DIDO system comprises that one has the base station of spaced antenna, the Radio Resource that this base station is same as traditional SIO system in utilization (, identical time slot duration and frequency band), send parallel data stream (through precoding) to a plurality of users, to strengthen downlink throughput.S.G. the application No.10/902 that is entitled as " System and Method for Distributed Input-Distributed Output Wireless Communications " that Perlman and T.Cotter submitted to July 30 in 2004,978 (" in firsts to file ") have provided the detailed description of DIDO system, this application has been transferred to the application's assignee, and this application is incorporated into this as a reference.
Exist various ways to realize the DIDO precoder.A kind of scheme is the block diagonalization (BD) described in following information: Q.H.Spencer, A.L.Swindlehurst and M.Haardt, " Zero forcing methods for downlink spatial multiplexing in multiuser MIMO channels; " IEEE Trans.Sig.Proc, vol.52, pp.461-471, Feb.2004; K.K.Wong, R.D.Murch, and K.B.Letaief, " A joint channel diagonalization for multiuser MIMO antenna systems, " IEEE Trans.Wireless Comm., vol.2, pp.773-786, JuI2003; L.U.Choi and R.D.Murch, " A transmit preprocessing technique for multiuser MIMO systems using a decomposition approach, " IEEE Trans.Wireless Comm., vol.3, pp.20-24, Jan2004; Z.Shen, J.G.Andrews, R.W.Heath and B.L.Evans, " Low complexity user selection algorithms for multiuser MIMO systems with block diagonalization; " be accepted and be published in IEEE Trans.Sig.Proc, Sep.2005; Z.Shen, R.Chen, J.G.Andrews, R.W.Heath and B.L.Evans, " Sum capacity of multiuser MIMO broadcast channels with block diagonalization, " is submitted to IEEE Trans.Wireless Comm., Oct.2005; R.Chen, R.W. Heath, with J.G. Andrews, " Transmit selection diversity for unitary precoded multiuser spatial multiplexing systems with linear receivers; " be accepted the Trans to IEEE, on Signal Processing, 2005.The method for the I/Q compensation given in these materials has been imagined the BD precoder, and this precoder can be expanded any type to the DIDO precoding.
In the DIDO-OFDM system, I/Q does not mate can cause two kinds of impact: ICI and inter-user interference.With similar in the SISO-OFDM system, the former is because the interference of adjusting from mirror image causes.The latter is due to the fact that and causes, I/Q does not mate the quadrature that can destroy the DIDO precoder, thereby produces and disturb between the user.Can, by method described herein, eliminate this two class at the transmitter and receiver place and disturb.Describe the method for three kinds of compensation of the I/Q for the DIDO-OFDM system at this, and do not mated for having and not thering is I/Q, compared their performance.Based on utilizing the performed emulation of DIDO-OFDM prototype and actual measurement, showed result.
Present embodiment is the expansion in first to file.Especially, these execution modes are relevant with the following characteristics in first to file:
System described in first to file, wherein the I/Q track can be subject to the impact of gain and unbalance in phase;
At the transmitter place, use the training signal adopted for channel estimating to calculate and there is the DIDO precoder that I/Q compensates; And
The signal characteristic data have been considered the distortion caused due to the I/Q imbalance, and, at the transmitter place, the method proposed according to this material, calculate the DIDO precoder by these signal characteristic data.
B,
embodiments of the present invention
At first, Mathematical Modeling of the present invention and framework will be described.
Before showing this programme, explain that the core mathematics concept is very useful.We make an explanation to it by hypothesis I/Q gain and unbalance in phase (do not comprise phase delay in this description, but this phase delay will be processed in the algorithm of DIDO-OFDM form automatically).For explaining basic thought, suppose that we want two plural s=s
i+ js
qand h=h
i+ jh
qmultiply each other, and make x=h*s.We represent the inphase quadrature component by subscript.Call following equation:
X
I=S
Ih
I-S
Qh
Q
And
x
Q=S
Ih
Q+S
Qh
I
Its matrix form can be rewritten as:
Carry out mark normalization conversion by channel matrix (H).Now suppose that s is sent symbol, and h is channel.Can carry out modeling to the existence of I/Q gain and unbalance in phase by creating following non-normalized conversion:
The effect of this skill is to confirm to be written as:
Now (A) rewritten:
We carry out giving a definition:
And
These two matrixes have the normalization structure, therefore can be represented as plural form:
h
e=h
11+h
22+j(h
21-h
12)
And
h
c=h
11-h
22+j(h
21+h
12)
By using all these knowledge, we can derive back effective equation and have two channel (equivalent channels h
ewith conjugation channel h
c) the scalar form.Therefore, the efficient transformation in (5) becomes:
x=h
es+h
cs
*
We are called equivalent channels by the first channel, and second channel is called the conjugation channel.If there is no I/Q gains and unbalance in phase, and this equivalence channel is the channel that we will observe.
By using similar argument, the Input output Relationship with the discrete time MIMON of I/Q gain and unbalance in phase * M system can be shown (by set up their matrix corresponding form by the scalar equivalent form of value):
Wherein, t is the discrete time index, h
e, h
c∈ C
m * N, s=[s
1..., s
n], x=[x
1..., x
m] and L be channel tap (channel tap) number.
In the DIDO-OFDM system, meaned the signal received in the frequency domain.If meet following equation, from the signal and systems re invocation:
FFT
k <s[t] }=S[k] FFT
k <s
*[t] }=S
*[(k)]=S
*[K-k] for k=0,1 ..., K-1
Utilize OFDM, for subcarrier k, the Input output Relationship of equal value of MIMO-OFDM system is:
Wherein, k=0,1 ..., K-1 is OFDM subcarrier index, H
eand H
crepresent respectively of equal value and conjugation channel matrix, be defined as follows:
And
(1) the second base value in is the interference of adjusting from mirror image.Can to it, be processed by building following repeatedly formula (stacked) matrix system (please carefully noting conjugate):
By using the method, can set up active matrix, to operate for DIDO.For example, utilize DIDO2 * 2 Input output Relationships (supposing that each user has single receive antenna), first user equipment can be considered following equation (when not having noise):
And the second user notes following equation:
Wherein,
represent respectively matrix H
eand H
cm capable, and w ∈ C
4x4for the DIDO pre-coding matrix.According to (2) and (3), can notice the symbol that user m receives
(that is the inter-carrier interference of, adjusting from mirror image (that is, for two interference sources that caused by the I/Q imbalance
and inter-user interference (that is,
and
, p ≠ m)) impact.(3) the DIDO pre-coding matrix W in is designed to eliminate this two distracters.
There are a plurality of different execution modes in the DIDO precoder can be used for herein, and this depends on the applied joint-detection in receiver place.In one embodiment, can adopt according to composite channel
(but not
) block diagonalization (BD) that calculates (for example refers to, Q.H.Spencer, A.L.Swindlehurst, and M.Haardt, " Zeroforcing methods for downlink spatial multiplexing in multiuser MIMO channels, " IEEE Trans.Sig.Proc, vol.52, pp.461-471, Feb.2004.K.K; Wong, R.D.Murch, and K.B.Letaief, " A joint channel diagonalization for multiuser MIMO antenna systems, " IEEE Trans.Wireless Comm., vol.2, pp.773-786, JuI2003; L. U.Choi and R.D.Murch, " A transmit preprocessing technique for multiuser MIMO systems using a decomposition approach, " IEEE Trans.Wireless Comm., vol.3, pp.20-24, Jan2004; Z.Shen, J.G. Andrews, R.W. Heath, with B.L Evans, " Low complexity user selection algorithms for multiuser MIMO systems with block diagonalization; " be accepted and be published in IEEE Trans.Sig.Proc, Sep.2005; Z.Shen, R.Chen, J.G. Andrews, R.W. Heath, and B.L Evans, " Sum capacity of multiuser MIMO broadcast channels with block diagonalization; " be submitted to IEEE Trans.Wireless Comm., Oct.2005).Therefore, the DIDO system is selected precoder at present, so that:
Wherein, α
i, jfor constant, and
the method is very useful, because by using this precoder, because the impact of having eliminated I/Q gain and unbalance in phase at the transmitter place fully can make to keep intact aspect other of DIDO precoder.
Also the DIDO precoder can be designed to eliminate in advance inter-user interference, and not eliminate in advance the ICI caused because of the IQ imbalance.Utilize the method, one of receiving filter that receiver (but not transmitter) can be by adopting the following stated compensates the IQ imbalance.Therefore, the Precoding Design standard in (4) can be modified to:
And
At receiver side, for to sending symbolic vector
estimated, user m adopts the ZF filter, and estimated symbolic vector is given as:
Although the easy to understand of ZF filter, receiver also can be applied other filters known in those skilled in the art of any amount.A kind of masses are chosen as the MMSE filter, wherein:
And ρ is signal to noise ratio.Alternatively, the user can carry out maximum likelihood symbol detection (or ball decoder, iteration change).For example, first user can be used the ML receiver, and solves following optimization:
Wherein, the set that S is all possible vectorial s, and depend on constellation sizes.This ML receiver provides performance preferably, but requires higher complexity at the receiver place.Similar one group of equation can be applicable to the second user.
Note, in (6) and (7)
with
be assumed to be and there is zero.This hypothesis is only in the situation that the emission precoder can be eliminated for the inter-user interference of the standard in (4) effective fully.Similarly,
with
only at the emission precoder, can eliminate in the situation of inter-carrier interference (that is, from mirror image adjust) fully is diagonal matrix.
Figure 13 has shown a kind of execution mode of the framework of the DIDO-OFDM system with I/Q compensation, and described DIDO-OFDM system comprises IQ-DIDO precoder 1302, the transmitting channel 1304 that is positioned at base station (BS), the channel estimating logical one 306 that is positioned at subscriber equipment and ZF, MMSE or ML receiver 1308.Described channel estimating logical one 306 via training signal to channel
with
estimated, and these estimations are fed back to the precoder in AP.BS calculates DIDO precoder weight (matrix W), disturbs with interference and the user who eliminates in advance because I/Q gains and unbalance in phase is caused, and data are sent to the user by wireless channel 1304.Subscriber equipment m adopts ZF, MMSE or ML receiver 1308, and the channel estimating provided by range site 1304 is eliminated residual interference, and data are carried out to demodulation.
Can adopt following three execution modes to realize this I/Q backoff algorithm.
Method 1-TX compensation: in this embodiment, transmitter calculates pre-coding matrix according to the standard in (4).At the receiver place, subscriber equipment adopts " simplification " ZF receiver, wherein
with
be assumed to be diagonal matrix.Therefore, formula (8) is reduced to:
Method 2-RX compensation: in this embodiment, transmitter is based on R.Chen, R.W.Heath, and J.G. Andrews, " Transmit selection diversity for unitary precoded multiuser spatial multiplexing systems with linear receivers; " accepted to IEEE Trans, on Signal Processing, the traditional B D method of describing in 2005, calculate pre-coding matrix, and for the standard in (4), do not eliminate intercarrier and inter-user interference.Utilize the method, the pre-coding matrix in (2) and (3) is reduced to:
At the receiver place, subscriber equipment adopts the ZF filter as in (8).Note, the method is such not as above-mentioned method 1, at the transmitter place, eliminates in advance interference.Therefore, it eliminates inter-carrier interference at the receiver place, but can not eliminate inter-user interference.In addition, require feedback than method 1
with
in method 2, the user only needs the vector of feedback for transmitter
to calculate the DIDO precoder.Therefore, method 2 is particularly suitable for having the DIDO system of low-rate feedback channel.On the other hand, method 2 needs the subscriber equipment place to have higher a little computation complexity, to calculate the ZF receiver in (8) (but not (11)).
Method 3-TX-RX compensation: in one embodiment, above-mentioned two methods are merged.Transmitter calculates pre-coding matrix as (4), and receiver is estimated sending symbol according to (8).
I/Q uneven (no matter being that unbalance in phase, gain are uneven, or be to postpone imbalance) can cause harmful degradation to the signal quality in wireless communication system.For this reason, circuit in the past all is designed to have lower imbalance.Yet, as mentioned above, can launch Digital Signal Processing and/or the specific receiver of precoded form by use, revise this problem.One embodiment of the present invention comprise the system with a plurality of new functional units, and each unit is for realizing that the I/Q correction in ofdm communication system or DIDO-OFDM communication system is all very important.
One embodiment of the present invention are used the precoding based on channel condition information, to eliminate the inter-carrier interference (ICI) (because I/Q does not mate and causes) of adjusting from mirror image in ofdm system.As shown in figure 11, the known precoding unit 1108 of a plurality of map unit 1106, DIDO IQ, a plurality of RF transmitter unit 1114, user feedback unit 1112 and the DIDO configurator unit 1110 that comprise subscriber selector unit 1102, a plurality of coded modulation unit 1104, correspondence according to the DIDO transmitter of present embodiment.
The feedback information that described subscriber selector unit 1102 obtains based on feedback unit 1112, select and a plurality of user U
1-U
mthe data that are associated, and this information is offered to each the coded modulation unit 1104 in a plurality of coded modulation unit 1104.Encoded and demodulation to each user's information bit in each coded modulation unit 1104, and they are sent to map unit 1106.This map unit 1106 maps to complex symbol by input bit, and result is sent to the known precoding unit 1108 of DIDO IQ.The channel condition information that the known precoding unit 1108 of this DIDO IQ utilizes feedback unit 1112 to obtain from the user, calculate the known precoding weight of DIDO IQ, and the incoming symbol of obtaining from map unit 1106 carried out to precoding.Each pre-code data stream is sent to OFDM unit 1115 by the known precoding unit 1108 of DIDO IQ, and this OFDM unit 1115 calculates IFFT, and adds Cyclic Prefix.This information is sent to D/A unit 1116, and this D/A unit 1116 carries out digital-to-analogue conversion, and sends it to RF unit 1114.This RF unit 1114 to intermediate frequency/radio frequency, and sends it to transmitting antenna by the baseband signal raising frequency.
Described precoder is adjusted and is operated together routine mediation mirror image, with compensation I/Q imbalance.The precoder design standard of any amount be can use, ZF, MMSE or weighting MMSE design comprised.In a preferred embodiment, precoder can remove fully because I/Q does not mate caused ICI, thereby makes receiver not need to carry out any ancillary relief.
In one embodiment, described precoder is used the block diagonalization standard, in the situation that not exclusively eliminate each user's I/Q, to affect (this needs accessory receiver to process), eliminates inter-user interference fully.In another embodiment, described precoder is eliminated inter-user interference and the ICI interference caused because of the I/Q imbalance fully by zero pressure standard.This execution mode can be used at the receiver place traditional DIDO-OFDM processor.
One embodiment of the present invention are used the precoding based on channel condition information, with eliminate the inter-carrier interference (ICI) adjusted from mirror image in the DIDO-OFDM system (because of I/Q do not mate caused), and each user adopts the known DIDO receiver of IQ.As shown in figure 12, in one embodiment of the invention, system (comprising receiver 1202) comprises a plurality of RF unit 1208, correspondingly a plurality of A/D unit 1210, IQ known channel estimator 1204 and DIDO feed back maker unit 1206.
Described RF unit 1208 receives the signal sent from DIDO transmitter unit 1114, and this signal down, to base band, and is offered to A/D unit 1210 by the signal after this frequency reducing.Afterwards, this signal of 1210 pairs of this A/D unit carries out analog-to-digital conversion, and sends it to OFDM unit 1213.This OFDM unit 1213 removes Cyclic Prefix, and carries out FFT, so that this signal is reported to frequency domain.During cycle of training, OFDM unit 1213 is sent to IQ known channel estimation unit 1204 by output, and this IQ known channel estimation unit 1204 calculates channel estimating in frequency domain.Alternatively, can in time domain, calculate described channel estimating.During the data cycle (data period), OFDM unit 1213 is sent to the known receiver unit 1202 of IQ by output.The known receiver unit of this IQ calculates the IQ receiver, and described signal is carried out to demodulate/decode, to obtain data 1214.Described IQ known channel estimation unit 1204 sends described channel estimating to DIDO feedback maker unit 1206, and this feedback maker unit 1204 can be quantized described channel estimating, and via FEEDBACK CONTROL channel 1112, it is beamed back to transmitter.
In one embodiment, determine the receiver coefficient with IQ known channel estimator 1204, to remove ICI.Therefore, we required the DIDO-OFDM system (inter-carrier interference (ICI) of using precoding based on channel condition information to eliminate to adjust from mirror image (and because of I/Q do not mate cause)), the rights and interests of the known DIDO receiver of IQ and IQ known channel estimator.Described channel estimator can be used traditional training signal, maybe can use the training signal of the special structure sent on the inphase quadrature signal.The algorithm for estimating of any amount be can implement, least square method, MMSE or maximum likelihood comprised.Described IQ known channel estimator provides input for the known receiver of IQ.
Channel condition information can be provided for website by channel reciprocity or by feedback channel.One embodiment of the present invention comprises the DIDO-OFDM system, and this system has the known precoder of I/Q, and for transferring to from the channel condition information of user's terminal the known feedback channel of I/Q of website.This feedback channel can be physics or logical control channel.It can be by special-purpose or shared in RACH.The DIDO feedback maker that can locate by user's terminal (we have also required the rights and interests of this user terminal) generates feedback information.Described DIDO feedback maker is using the output of described I/Q known channel estimator as input.But its quantized channel coefficient, maybe can be used any amount Limited Feedback algorithm known in the field.
User's distribution, modulation and encoding rate, can change according to the result of described DIDO feedback maker to the mapping of space-time frequency coding time slot.Therefore, one execution mode comprises the known DIDO configurator of IQ, this configurator is used from one or more users' IQ known channel and is estimated to configure the known precoder of DIDO IQ, the user's who selects modulation rate, encoding rate, permission to send subset and their mapping to the space-time frequency coding time slot.
In order to estimate the performance of proposed compensation method, will compare three DIDO2 * 2 systems:
1, having I/Q does not mate: sent by all tune (except adjusting at DC mediation edge), and I/Q is not mated and compensates;
2, there is the I/Q compensation: by all row of transferring in, send, and by using above-mentioned " method 1 " not mate and compensate I/Q;
3, desirable: as only by odd number, to transfer in row and send, to avoid inter-user interference and not mate intercarrier (that is, adjusting from the mirror image) interference caused because of I/Q.
After this, showed in true propagation situation and utilized the DIDO-OFDM prototype to be measured obtained result.Figure 14 has illustrated the 64-QAM planisphere obtained from above-mentioned three systems.These planispheres be in the situation that same customer location and fixedly average signal-to-noise ratio (~45dB) obtain.The first planisphere 1401 is very noisy (due to the interference from the mirror image tune of uneven cause of I/Q).The second planisphere 1402 shows some improvement (due to the I/Q compensation).Note, the second planisphere 1402 is the ideal situation shown in planisphere 1403 pure like that (owing to there being the phase noise that may produce inter-carrier interference (ICI)) not.
Figure 15 shows to have and not to have in the unmatched situation of I/Q, the average SER (symbol error rate) 1501 of the DIDO2 of 64-QAM and 3/4 encoding rate * 2 systems and every user's goodput (goodput) 1502.The OFDM bandwidth is 250KHZ, has 64 and adjusts and circulating prefix-length L
cp=4.Due in the ideal case, we only send data by the subset of adjusting, and therefore according to the transmitting power (but not total transmitting power) of average every tune, estimate SER and goodput performance, to guarantee the fair comparison between different situations.In addition, in following result, we use the normalized value (indicating with decibel) of transmitting power, because the target of ours is (but not definitely) relatively performance of comparison different schemes herein.Figure 15 shows and exists in the unbalanced situation of I/Q, the saturated and miss the mark SER (~10 of SER
-2), this and A.Tarighat and A.H.Sayed, " MIMO OFDM receivers for systems with IQ imbalances, " IEEE Trans.Sig.Proc, vol.53, pp.3583-3596, the result of reporting in Sep.2005 is consistent.This saturation effect is due to the fact that and causes, and signal power and interference power (from mirror image, adjusting) increase along with the increase of TX power.Yet, pass through proposed I/Q compensation method, can eliminate interference, and obtain SER performance preferably.Note, because the 64-QAM modulation needs larger transmitting power, therefore, can cause SER can there is trickle increase at high SNR place because of the amplitude saturation effect in DAC.
In addition, can be observed, in the situation that there is the I/Q compensation, the SER performance approaches ideal situation very much.Between these two kinds of situations, the 2dB gap of TX power is because phase noise (this phase noise may produce additional interference between adjacent OFDM is adjusted) causes.Finally, goodput curve 1502 shows when application I/Q method, and it can send the data of twice than ideal situation, because we have used all data tune, only odd number is adjusted (for ideal situation).
Figure 16 illustrates in the situation that have the I/Q compensation or do not have I/Q compensation, the SER performance of different Q AM planisphere.We can be observed, and in this execution mode, the method proposed is particularly advantageous for the 64-QAM planisphere.For 4-QAM and 16-QAM, I/Q compensation method meeting produces than having the worse performance of the unmatched situation of I/Q, and this may be because the interference elimination that the method proposed requires larger power to carry out the data transmission and adjusts from mirror image.In addition, due to the larger minimum range between constellation point, 4-QAM and 16-QAM also are subject to the unmatched impact of I/Q like that not as 64-QAM.Referring to A.Tarighat, R.Bagheri, and A.H.Sayed, " Compensation schemes and performance analysis of IQ imbalances in OFDM receivers; " Signal Processing, IEEE Transactions on[also can be referring to Acoustics, Speech, and Signal Processing, IEEE Transactions on], vol.53, pp.3257-3268, Aug.2005.Observable Figure 16 compare and draw this conclusion by I/Q not being mated with ideal situation for 4-QAM and 16-QAM also.Therefore, for the situation of 4-QAM and 16-QAM, have and disturb the needed secondary power of DIDO precoder of eliminating (adjusting from mirror image) not go bail for for the slight interests of I/Q compensation.Note, can solve this problem by adopting above-mentioned I/Q compensation method 2 and 3.
Finally, under different propagation conditions, measured the relative SER performance of above-mentioned three methods.Also described and had the SER performance of the unmatched situation of I/Q, for your guidance.It is 450.5MHZ and bandwidth 64-QAM DIDO2 * 2 systems that are 250KHz that Figure 17 has illustrated for carrier frequency, at two SER that different customer locations is measured.In position 1, the user with in chummery not and the BS in NLOS (ignore apart from) state at a distance of~6 λ.In position 2, user and the BS with LOS (sighting distance) are at a distance of~λ.
Figure 17 shows all three kinds of compensation methodes and all has outstanding performance than situation about not compensating.Yet, it should be noted, under any channel conditions, method 3 all surpasses other two kinds of compensation methodes.Method 1 and 2 relative performance depend on propagation condition.By the actual measurement activity, can show that method 1 surpasses method 2 substantially, because it has eliminated the inter-user interference that (at the transmitter place) I/O imbalance causes in advance.When this inter-user interference is very little, as shown in the curve chart 1702 of Figure 17, method 2 can surpass method 1, because it can not suffer the power loss caused because of I/Q compensation precoder.
Up to the present, by only considering limited group of propagation situation (as shown in figure 17), distinct methods is compared.After this, measure the relative performance of these methods in desirable i.i.d. (the same distribution of independence and tool) channel.Utilization transmits and receives I/Q phase place and the gain imbalance of side and carrys out emulation DIDO-OFDM system.Figure 18 shows in the situation that only launch pusher side has gain balance (that is, have gain 0.8 on the I of the first transmitting chain rail, have gain 1 on other rails), the performance of the method proposed.Can find out, method 3 has surpassed every other method.In addition, obtain results with 2 places, position in the curve chart 1702 of Figure 17 and compare, in the i.i.d. channel, method 1 comparable method 2 is carried out better.
Therefore, provided three kinds of novel methods and compensated the I/Q imbalance in above-mentioned DIDO-OFDM system, method 3 surpasses other proposed compensation methodes.In having the system of low-rate feedback channel, but using method 2 reduces the required feedback quantity of DIDO precoding, but can cause poor SER performance.
II,
self adaptation DIDO delivery plan
Use description to strengthen another execution mode of system and method for the performance of distributed input distributed output (DIDO) system.The channel status that the method changes by tracking, dynamically give different subscriber equipmenies by allocation of radio resources, to increase throughput when meeting some target error rate.Described subscriber equipment is estimated channel quality, and it is fed back to base station (BS); This base station is processed the channel quality that is obtained from subscriber equipment, to select the optimal user cluster tool, DIDO scheme, modulation/coding scheme (MCS) and the array configurations that send for next time; Described base station is sent to parallel data via precoding a plurality of subscriber equipmenies, and signal is demodulated at the receiver place.
Also describe one for the system of the effective Resources allocation of DIDO wireless link.This system comprises that the ,Gai base station, DIDO base station with DIDO configurator is processed the feedback that receives personal family, to select the optimal user set, DIDO scheme, modulation/coding scheme (MCS) and the array configurations that send for next time; Receiver in the DIDO system, this receiver is measured channel and other relevant parameters, to generate the DIDO feedback signal; And DIDO FEEDBACK CONTROL channel, for will be from user's transmission of feedback information to base station.
As detailed in the following, some notable features of this execution mode of the present invention can include, but are not limited to:
Be used for based on channel quality information, select adaptively number of users, DIDO delivery plan (, it line options or multiplexing), modulation/coding scheme (MCS) and array configurations, to minimize SER, or maximize every user's spectrum efficiency or the technology of downlink tone spectrum efficiency;
The sending modes of group DIDO more than being used for defining are usingd as the technology of the combination of DIDO scheme and MCS;
For according to channel status, different DIDO patterns being assigned to the technology of different time slots, OFDM mediation DIDO subflow;
Different DIDO patterns dynamically are assigned to the technology of different user for the channel quality based on different user;
For the standard that switching is activated to self adaptation DIDO of the link quality metric based on calculating in time domain, frequency domain and spatial domain;
For based on look-up table, self adaptation DIDO being switched the standard activated.
As shown in figure 19 there is the DIDO system of DIDO configurator at base station place, this system can be based on channel quality information, select adaptively number of users, DIDO delivery plan (, it line options or multiplexing), modulation/coding scheme (MCS) and array configurations, to minimize SER, or maximize every user's spectrum efficiency or downlink tone spectrum efficiency;
Thering is the DIDO configurator at base station place and thering is the DIDO system of DIDO feedback maker at each subscriber equipment place as shown in figure 20, this system is used other parameters (being similar to estimated SNR) at estimated channel conditions and/or receiver place, inputs to the feedback message of DIDO configurator with generation.
The DIDO system, this system has DIDO configurator (at the place, base station), DIDO feedback maker and DIDO FEEDBACK CONTROL channel (this DIDO feedback channel is for transferring to base station by the DIDO specific configuration information from the user).
A,
background
In multiple-input and multiple-output (MIMO) system, (for example can conceive diversity scheme, orthogonal space time packet (OSTBC) is (referring to V.Tarokh, H.Jafarkhani, and A.R.Calderbank, " Spacetime block codes from orthogonal designs, " IEEE Trans.Info.Th., vol.45, pp.1456-467, JuI.1999) or day line options (referring to R.W.Heath Jr., S.Sandhu, and A.J.Paulraj, " Antenna selection for spatial multiplexing systems with linear receivers, " IEEE Trans.Comm., vol.5, pp.142-144, Apr.2001), to prevent fading channel, improve link reliability (this reliability can be exchanged into better coverage rate).On the other hand, spatial reuse (SM) can be usingd a plurality of parallel datas and sent and strengthen throughput of system as means.Referring to G.J.Foschini, G.D.Golden, R.A.Valenzuela, and P.W.Wolniansky, " Simplified processing for high spectral effciency wireless communication employing multielement arrays, " IEEE Jour.Select.Areas in Comm., vol.17, no.11, pp.1841-1852, Nov.1999.According to deriving from L.Zheng and D.N.C.Tse, " Diversity and multiplexing: a fundamental tradeoff in multiple antenna channels; " IEEE Trans.Info.Th., vol.49, no.5, pp.1073-1096, the theoretical diversity of May2003/multiplexing compromise, these benefits can realize in mimo system simultaneously.The channel status of one actual form of implementation for changing by tracking carries out the self adaptation switching between diversity and multiplexing delivery plan.
A large amount of adaptive MIMO transmission technologies have now been proposed.R.W.Heath and A.J.Paulraj, " Switching between diversity and multiplexing in MIMO systems; " IEEE Trans.Comm., vol.53, no.6, pp.962-968, the diversity in Jun.2005/multiplexing changing method is designed to based on instantaneous channel quality information, improves the BER (bit error rate) sent for fixed rate.Alternatively, can be as S.Catreux, V.Erceg, D.Gesbert, and R.W.Heath.Jr., " Adaptive modulation and MIMO coding for broadband wireless data networks, " IEEE Comm.Mag., vol.2, pp.108-115, in June2002 (" Catreux "), like that, adopt statistic channel information to be activated self adaptation, thereby reduce the quantity of feedback overhead and control message.When the self adaptation transmission algorithm in Catreux is designed to based on channel/frequency selects designator, for the predeterminated target error rate in OFDM (OFDM) system, strengthens spectrum efficiency.Also, for narrowband systems, proposed similarly to hang down the feedback adaptive method, the method utilizes the channel space selectivity to be switched between diversity scheme and spatial reuse.Referring to for example A.Forenza, M.R.McKay, A.Pandharipande, R.W.Heath.Jr., and I.B.Collings, " Adaptive MIMO transmission for exploiting the capacity of spatially correlated channels, " accepted to the IEEE Trans, on Veh.Tech., Mar.2007; M.R.McKay, I.B.Collings, A.Forenza, and R.W.Heath.Jr., " Multiplexing/beamforming switching for coded MIMO in spatially correlated Rayleigh channels; " be accepted the Trans to IEEE, on Veh.Tech., Dec.2007; A.Forenza, M.R.McKay, R.W.Heath.Jr., and I.B.Collings, " Switching between OSTBC and spatial multiplexing with linear receivers in spatially correlated MIMO channels, " Proc.IEEE Veh.Technol.Conf., vol.3, pp.1387-1391, May2006; M.R.McKay, I.B.Collings, A.Forenza, with R.W.Heath Jr., " A throughput-based adaptive MIMO BICM approach for spatially correlated channels, " appears at Proc.IEEE ICC, June2006.
In this data, we extend to the DIDO-OFDM system by the working range represented in various previous disclosing.Referring to for example R.W.Heath and A.J.Paulraj, " Switching between diversity and multiplexing in MIMO systems, " IEEE Trans.Comm., vol.53, no.6, pp.962-968, Jun.2005; S.Catreux, V.Erceg, D.Gesbert, with R.W.Heath Jr., " Adaptive modulation and MIMO coding for broadband wireless data networks, " IEEE Comm.Mag., vol.2, pp.108-115, June2002; A.Forenza, M.R.McKay, A.Pandharipande, R.W.Heath Jr., and I.B.Collings, " Adaptive MIMO transmission for exploiting the capacity of spatially correlated channels, " IEEE Trans, on Veh.Tech., vol.56, n.2, pp.619-630, Mar.2007; M.R.McKay, I.B.Collings, A.Forenza, with R.W.Heath Jr., " Multiplexing/beamforming switching for coded MIMO in spatially correlated Rayleigh channels; " be accepted the Trans to IEEE, on Veh.Tech., Dec.2007; A.Forenza, M.R.McKay, R.W.Heath Jr., and I.B.Collings, " Switching between OSTBC and spatial multiplexing with linear receivers in spatially correlated MIMO channels, " Proc.IEEE Veh.Technol.Conf., vol.3, pp.1387-1391, May2006; M.R.McKay, I.B.Collings, A.Forenza, with R.W.Heath Jr., " A throughput-based adaptive MIMO BICM approach for spatially correlated channels, " appears at Proc.IEEE ICC, June2006.
Described NEW ADAPTIVE DIDO sending strategy at this, this strategy is usingd and is switched as a kind of means and carry out the improved system performance between the transmitting antenna of the user of varying number, varying number and delivery plan based on channel quality information.Note, M.Sharif and B.Hassibi, " On the capacity of MIMO broadcast channel with partial side information, " IEEE Trans.Info.Th., vol.51, p.506522, Feb.2005 and W.Choi, A.Forenza, J.G.Andrews, with R.W.Heath Jr., " Opportunistic space division multiple access with beam selection, " appear at IEEE Trans, the scheme of adaptively selected user in multi-user MIMO system has been proposed on Communications.Yet, opportunistic (opportunistic) space division multiplexing access (OSDMA) scheme during these are open is designed to by utilizing multi-user diversity to maximize total capacity, and they only can realize the part of theory capacity of dirty paper (dirty paper) code, because at the transmitter place, do not eliminate fully in advance interference.In DIDO transmission algorithm described herein, adopt block diagonalization to eliminate in advance inter-user interference.Yet the self adaptation sending strategy that proposes can be applied to any DIDO system, without the type of considering precoding technique.
Present patent application has been described the invention described above and, in the expansion of the execution mode of first to file, has been included but not limited to following supplementary features:
1, can adopt the training symbol for channel estimating in first to file to be estimated the link quality metric of self adaptation DIDO scheme by wireless client device.
2,, as described in first to file, base station receives the signal characteristic data from client device.In current execution mode, the signal characteristic data are defined for the link quality metric that self adaptation is activated.
3, described one for selecting the mechanism of antenna and number of users in first to file, and defined throughput distribution.In addition, can, as in first to file, the throughput of different stage dynamically be assigned to different clients.Current execution mode of the present invention has defined the novel standard relevant to this selection and throughput distribution.
B,
embodiments of the present invention
The target of the self adaptation DIDO technology proposed is for strengthening every user's spectrum efficiency or downlink tone spectrum efficiency to the different user in system by the Radio Resource dynamic assignment by time, frequency and space.This integral body self adaptation standard, for when meeting target error rate, improves throughput.According to spread state, also can improve by this adaptive algorithm user's link-quality (or coverage rate) via diversity scheme.The flow chart description that Figure 21 shows the step of self adaptation DIDO scheme.
2102, base station (BS) collects the channel condition information from all users.2104, according to received CSI, link quality metric is calculated in time domain/frequency domain/spatial domain in base station.2106, with these link quality metric select will be in next transmission serviced user, and for each user's sending mode.Note, sending mode comprises the various combination of modulation/coding and DIDO scheme.Finally, send data to the user at 2108, BS via the DIDO precoding.
2102, the base station selected channel condition information from all subscriber equipmenies (CSI).2104, the instantaneous of all subscriber equipmenies or statistical channel quality are determined with this CSI in base station.In the DIDO-OFDM system, can to channel quality (or link quality metric), be estimated in time domain, frequency domain and spatial domain.Afterwards, 2106, the optimal user subset is determined by link quality metric and for the sending mode of current spread state in base station.The set of DIDO sending mode is combined into the combination of DIDO scheme (that is, day line options or multiplexing), modulation/coding scheme (MCS) and array configurations.2108, by using selected user quantity and sending mode, send data to subscriber equipment.
Can carry out model selection by look-up table (LUT) (this look-up table be based on bit error rate performance in the different communication environments of DIDO system be pre-calculated).These LUT map to bit error rate performance by channel quality information.In order to build LUT, can estimate the DIDO system according to SNR and propagate bit error rate performance in situation in difference.Can find out from ber curve, can calculate the minimum SNR that realizes that a certain predeterminated target error rate is required.We are the SNR threshold value by this SNR requirement definition.Afterwards, estimate the SNR threshold value in different propagation situations and for different DIDO sending modes, and it is stored in LUT.For example, can build LUT by SER result in Figure 24 and Figure 26.Afterwards, according to this LUT, the sending mode for active user can be selected in base station, and this pattern can improve throughput when meeting the predeterminated target error rate.Finally, base station sends data to selected user via the DIDO precoding.Note, different DIDO patterns can be assigned to different time slots, OFDM tune and DIDO subflow, so that can carry out self adaptation in time domain, frequency domain and spatial domain.
Figure 19-Figure 20 has shown a kind of execution mode that adopts the adaptive system of DIDO.Introduce some new functional units and implemented proposed DIDO adaptive algorithm.Particularly, in one embodiment, the channel quality information 1912 that DIDO configurator 1910 can provide based on subscriber equipment, carry out several functions, comprise and select number of users, DIDO delivery plan (that is, day line options and multiplexing), modulation/coding scheme (MCS) and array configurations.
The feedback information of subscriber selector unit 1902 based on being obtained by DIDO configurator 1910, select and a plurality of user U
1-U
mthe data that are associated, and provide each the coded modulation unit in every a plurality of coded modulation unit 1904 by this information.Encoded and modulated each user's information bit in each coded modulation unit 1904, and they are sent to map unit 1906.This map unit 1906 maps to complex symbol by input bit, and sends it to precoding unit 1908.Coded modulation unit 1904 and map unit 1906 are all utilized the information that is obtained from DIDO configurator unit 1910, are chosen as the modulation/coding scheme type that each user adopts.Described information can be calculated by the channel quality information by each user of utilizing feedback unit 1912 and providing by configurator unit 1910.DIDO precoding unit 1908 utilizes the information of being obtained by DIDO configurator unit 1910 to calculate the DIDO precoding weight, and the incoming symbol that is obtained from map unit 1906 is carried out to precoding.By DIDO precoding unit 1906, the data flow after each precoding is sent to OFDM unit 1915, this OFDM unit 1915 calculates IFFT and adds Cyclic Prefix.This information is sent to D/A unit 1916, and this D/A unit 1916 carries out digital-to-analogue conversion, and final analog signal is sent to RF unit 1914.This RF unit 1914 to intermediate frequency/radio frequency, and sends it to transmitting antenna by the baseband signal raising frequency.
The RF unit 2008 of each client device receives the signal sent from DIDO transmitter unit 1914, and this signal down, to base band, and is offered to A/D unit 2010 by the signal after frequency reducing.Afterwards, this A/D unit 2010 is converted to numeral by this signal from analog, and sends it to OFDM unit 2013.This OFDM unit 2013 removes Cyclic Prefix, and carries out FFT, so that signal is reported to frequency domain.In cycle of training, OFDM unit 2013 is sent to channel estimating unit 2004 by output, and this channel estimating unit 2004 is calculated channel estimating in frequency domain.Alternatively, can calculate channel estimating in time domain.During the data cycle, OFDM unit 2013 is sent to receiver unit 2002 by output, and 2002 pairs of signals of this receiver unit carry out demodulate/decode, to obtain data 2014.Described channel estimating unit 2004 is sent to DIDO feedback maker unit 2006 by channel estimating, and this DIDO feedback maker unit 2006 can be quantized channel estimating, and via FEEDBACK CONTROL channel 1912, it is beamed back to transmitter.
Described DIDO configurator 1910 can be used the information obtained at the place, base station, or in a preferred embodiment, the extra output of using the DIDO feedback maker 2006 (referring to Figure 20) that works in each subscriber equipment place.The channel conditions 2004 that these DIDO feedback maker 2006 use are estimated and/or other parameters that are similar to estimated SNR at receiver place generate the feedback message that will be input to DIDO configurator 1910.Described DIDO feedback maker 2006 can be compressed, be quantized information at the receiver place and/or be used Limited Feedback strategies more known in the field.
Described DIDO configurator 1910 can be used the information of recovering from DIDO FEEDBACK CONTROL channel 1912.DIDO FEEDBACK CONTROL channel is the logic OR physical control channel, and the output that this channel can be used for DIDO is fed back maker 2006 is sent to base station from the user.Control channel 1912 can be implemented in the mode known in the field of any amount, and can be the logic OR physical control channel.As physical channel, it can comprise the dedicated time slot that is assigned to the user/frequency gap.Its shared RACH of all users of also can serving as reasons.Described control channel can be by pre-assigned, or can in existing control channel, create by the bit (stealing bits) of occupying of predetermined way.
In the following discussion, will in true communication environments, describe by utilizing the DIDO-OFDM prototype to be measured obtained result.These results have shown the realizability of potential gain in self adaptation DIDO system.At first the performance that represents different stage DIDO system, show to increase antenna/user quantity, to realize larger downlink throughput.Afterwards, describe the DIDO performance relevant with the position of subscriber equipment, show the channel status that the needs tracking changes.Finally, the performance of the DIDO system that adopts diversity technique is described.
The performance of i, different stage DIDO system
Utilize increasing transmitting antenna (N=M, wherein M is number of users) to estimate the performance of different DIDO systems.The performance of following system is compared: SISO, DIDO2 * 2, DIDO4 * 4, DIDO6 * 6 and DIDO8 * 8.DIDON * M refers to have at the BS place N transmitting antenna and M user's DIDO.
Figure 22 has shown the transmit/receive antenna layout.Configure to arrange transmitting antenna 2201 with square array, and the user is positioned at around emission array.At Figure 22, T refers to " emission " antenna, and U refers to " subscriber equipment " 2202.
Different antennae subset in 8 yuan of emission arrays is in active state, and this depends on the N value selected for different measuring.For each DIDO rank (N), selection can to the constraint of the fixed size of 8 element array for the antenna subset that covered of the true area of maximum.This standard is supposed to strengthen the space diversity of given N value.
Figure 23 shows for different other array configurations of DIDO level that are applicable to available true area (that is, dotted line).Square empty frame has 24 " * 24 " size, corresponding to the 450MHz carrier frequency~λ * λ.
Commentary based on relevant to Figure 23 and with reference to Figure 22, now will define and following system in the performance of each system:
SISO (2301) with T1 and U1
There is T1,2 and U1,2 DIDO2 * 2 (2302)
There is T1,2,3,4 and U1,2,3,4 DIDO4 * 4 (2303)
There is T1,2,3,4,5,6 and U1,2,3,4,5,6 DIDO6 * 6 (2304)
There is T1,2,3,4,5,6,7,8 and U1,2,3,4,5,6,7,8 DIDO8 * 8 (2305)
Figure 24 shows in 4-QAM and 1/2FEC (forward error correction) rate situation, the functional relation of SER, BER, SE (spectrum efficiency) and goodput performance and emission (TX) power in above-mentioned DIDO system.Observation draws, SER and BER performance can descend because the N value increases.This impact is caused by following two phenomenons: for fixing TX power, the input power of DIDO array can be divided between increasing user's (or data flow); Space diversity can reduce along with the increase of the number of users in actual DIDO channel.
As shown in figure 24, in order to compare the relative performance of different stage DIDO system, target BER is fixed as to 10
-4(this value can change according to system), this is worth roughly corresponding to SER=10
-2.We will be referred to as corresponding to the TX performance number of this target TX power threshold (TPT).For any N, if TX power lower than TPT, we suppose under the DIDO level n, to be sent, and we need to switch to other DIDO of even lower level.In addition, at Figure 24, observable draws, when TX power surpasses the TPT for any N value, SE and goodput performance can reach capacity.According to these results, the self adaptation sending strategy can be designed between different stage DIDO, switched, to strengthen for fixedly SE or the goodput of the predeterminated target error rate.
Performance under ii, user variable situation
The target of this test is, via carry out emulation in the space correlation channel, estimates the DIDO performance of different user position.DIDO2 * 2 systems are regarded as having 4QAM and 1/2FEC leads.As shown in figure 25, user 1 is positioned at the side of emission array and penetrates (broadside) direction, and user 2 position is penetrated direction from side and become end-fire (endfire) direction.Transmitting antenna interval-λ/2, and-2.5 λ of being separated by with the user.
Figure 26 shows the diverse location for subscriber equipment 2, SER and every user's SE result.Penetrate orientation measurement from the limit of emission array, the arrival angle (AOA) of subscriber equipment is 0 ° to 90 °.Observation draws, along with the angular distance of subscriber equipment increases, the DIDO performance will promote, because the DIDO channel memory is in larger diversity.In addition, at target SER=10
-2, there is the gap of 10dB in place between AOA2=0 ° and AOA2=90 ° of both of these case.This result with in Figure 35 for 10 ° of angle spread to obtain simulation result consistent.In addition, note, for the situation of AOA1=AOA2=0 °, may have coupling effect (causing because their antenna is adjoining) between two users, this may make their performance different from the simulation result in Figure 35.
Iii, for the preferred situation of DIDO8 * 8
Figure 24 has shown that DIDO8 * 8 produce the SE larger than even lower level DIDO, but has higher TX power demand.The target of this analysis is to illustrate this situation that exists, and DIDO8 * 8 not only aspect peaks spectrum efficiency (SE), but also, aspect TX power demand (or TPT), surpass DIDO2 * 2, to realize described peak value SE.
Note, in i.i.d. (ideal) channel, the gap of TX power existence~6dB between the SE of DIDO8 * 8 and DIDO2 * 2.This gap causes because of this fact, and DIDO8 * 8 are cut apart TX power between 8 data flow, and DIDO2 * 2 are only cut apart between two stream.This result is illustrated via the emulation in Figure 32.
Yet, in the space correlation channel, the function that TPT is communication environments characteristic (for example, array is towards, customer location, angle spread).For example, Figure 35 show for the low angle between two different user devices positions expansion~the 15dB gap.Showed similar result in the application Figure 26.
Be similar to mimo system, when the user is positioned at the end-on direction of TX array, the performance of DIDO system can descend (because lacking diversity, causing).This impact can draw by utilizing current DIDO prototype to be measured to observe.Therefore, a kind of DIDO8 of illustrating * 8 surpass the mode of DIDO2 * 2 for the user is placed in to the end-on direction with respect to DIDO2 * 2 arrays.In this situation, DIDO8 * 8 have surpassed DIDO2 * 2, because the 8-aerial array provides higher diversity.
In this is analyzed, considered following system:
The DIDO8 of system 1:4-QAM * 8 (every time slot sends 8 parallel data streams);
The DIDO2 of system 2:64-QAM * 2 (every 4 time slots once send sending user X and Y).For this system, we consider four kinds of combinations of TX and RX aerial position: a) T1, T2U1,2 (end-on directions); B) T3, T4U3,4 (end-on directions); C) T5, T6U5,6 (being separated by with end-on direction~30 °); D) T7, T8U7,8 (NLOS (ignoring distance));
The DIDO8 of system 3:64-QAM * 8; And
The MISO8 of system 4:64-QAM * 1 (every 8 time slots once send sending user X).
For all these situations, use 3/4 FEC to lead.
Figure 27 has illustrated user's position.
In Figure 28, the SER result shows due to the gap of a~15dB between system 2a and 2c of different array directions and customer location (similar to the simulation result in Figure 35).The first subgraph in the second row shows the value (that is, corresponding to BER1e-4) of the TX power that the SE curve is saturated.We observe system 1 and have produced each larger user SE than system 2 for lower TX power demand (being less than~5dB).And, due to the spatial multiplexing gain of DIDO8 * 8 on DIDO2 * 2, DIDO8 * 8 are more obvious for DL (down link) SE and DL goodput than the benefit of DIDO2 * 2.Due to the array gain (that is, having the MRC of MISO8 * 1) of beam forming, system 4 has lower TX power demand (being less than 8dB) than system 1.But system 4 than system 1, only produced each user SE 1/3., system 2 than the poor performance of system 1 (that is having produced lower SE for larger TX power demand).Finally, system 3 has produced much bigger SE (due to larger exponent number (larger order) modulation) than system 1 for larger TX power demand (~15dB).
According to these results, can infer to draw a conclusion:
A kind of channel conditions is confirmed to be DIDO8 * 8 surpasses DIDO2 * 2 (for lower TX power demand, having produced larger SE);
In this channel conditions, DIDO8 * 8 have produced each larger user SE and DL SE than DIDO2 * 2 and MISO8 * 1; And
Can use high order modulation (be 64-QAM, rather than 4-QAM) as cost and further increase the performance of DIDO8 * 8 by take larger TX power demand (being greater than~15dB).
Iv. the DIDO that there is day line options
Below, we are evaluated at the benefit of the Antenna Selection Algorithem of describing in " the Transmit selection diversity for unitary precoded multiuser spatial multiplexing systems with linear receivers " that delivered by R.Chen, R.W.Heath and J.G.Andrews in 2005 on Signal Processing received by the IEEE journal.We lead to present the result for a specific DIDO system with the FEC of two users, 4-QAM and 1/2.Following system is compared in Figure 27:
There is T1,2 and U1,2 DIDO2 * 2; And
There is T1,2,3 and U1, the DIDO3 of 2 use sky line options * 2.
Position of transmitting antenna and user device location are with identical in Figure 27.
Figure 29 shows DIDO3 with day line options * 2 gain of can provide~5dB is provided with DIDO2 * 2 systems (not having selection).Notice that channel is almost static (there is no Doppler effect), so selection algorithm is applicable to path loss and channel space-related, rather than decay fast.We should see different gains in having much higher general situation of strangling effect.And, in this particular experiment, observe Antenna Selection Algorithem and select antenna 2 and 3 for sending.
Iv. for the SNR threshold value of LUT
Selecting [0171], we have stated that model selection realizes by LUT.LUT can come by precomputation with realization specific predefined target error rate performance for the DIDO sending mode in different communication environments by assessment SNR threshold value.Below, we provide the performance that has and do not have the DIDO system of day line options and transformable number of users, and described performance can be as the guidance of structure LUT.Although Figure 24, Figure 26, Figure 28, Figure 29 are by obtaining with the actual measurement of DIDO prototype, following figure obtains by emulation.Following BER result hypothesis does not have FEC.
Figure 30 shows the average BER performance of DIDO pre-coding schemes different in the independent same distribution channel.The curve that indicates " not having to select " refers to the situation of using BD.In same figure, the performance of day line options (ASel) is illustrated for the additional antenna (for the user of varying number) of varying number.Can find out, along with the quantity growth of additional antenna, ASel provides better diversity gain (the BER slope of a curve in Yi Gao SNR district is feature), has produced better covering.For example,, if we are fixed to 10 by target BER
-2(for the actual value of uncoded system), the SNR provided by ASel gain is along with the quantity growth of antenna.
Figure 31 shows the SNR gain for the ASel of the function of the quantity of the extra transmitting antenna of conduct in the independent same distribution channel of different target BER.Can find out, only by adding 1 or 2 antenna, ASel compares with BD and has produced huge SNR gain.In following part, we will be only for the situation of 1 or 2 additional antenna by target BER is fixed to 10
-2(for uncoded system) assesses the performance of ASel.
Figure 32 shows the SNR threshold value for the function as number of users (M) of the BD that has 1 and 2 additional antenna in the independent same distribution channel and ASel.We observe the larger reception SNR demand due to the user for larger amt, and the SNR threshold value is along with M increases.Note, we suppose that the user for any amount is fixing total transmitting power (with the transmitting antenna of varying number).In addition, Figure 32 shows because the gain of sky line options is constant for the user of any amount in the independent same distribution channel.
Below, we show the performance of the DIDO system in spatial correlation channel.We are by each user's of COST-259 spatial Channel Model emulation of describing in " the Channel models for link and system level simulations " that deliver on IEEE802.16Broadband Wireless Access Working Group in September, 2004 at X.Zhuang, F.W. Vook, K.L. Baum, T.A.Thomas and M.Cudak channel.We generate the single group for each user.As a kind of case study, we have supposed the NLOS channel, at transmitter, uniform linear array (ULA) are arranged, and element spacing is 0.5 λ.For the situation of 2 custom systems, we carry out emulation group with the AOA1 arrived and the average angle of AOA2 respectively for the first and second users.AOA is with respect to the side surface direction of ULA and measured.As the user who has in system more than two, we generate has at scope [φ
m, φ
m] in user's the group of evenly spaced average A OA, wherein our definition
K is user's quantity, and Δ φ is the angular distance between user's average A OA.Note angular range [φ
m, φ
m] center is 0 °, corresponding to the side of ULA, penetrates direction.Below, we with BD and ASel delivery plan and different numbers of users study as channel angle distribute (AS) and the user between the BER performance of DIDO system of function of angular distance.
Figure 33 shows the BER of the average SNR with respect to each user of two users with different AS values for being positioned at same angle direction (with respect to the side of ULA, penetrating direction, AOA1=AOA2=0 °).Can find out, along with AS increases, BER performance improvement and approach the independent same distribution situation.In fact, higher AS has produced less covering between two users' feature mode and the better performance of BD precoder on statistics.
Figure 34 shows the result similar to Figure 33, but has higher angular distance between the user.We consider AOA1=0 °, AOA2=90 ° (i.e. 90 ° of angular distances).In the situation that low AS has realized best performance.In fact, for the situation of high angular distance, when angular distance is low, less crossover is arranged between user's feature mode.What is interesting is, we observe for the identical reason of just having mentioned, and the BER performance in low AS is better than the independent same distribution channel.
Next, for 10 in different relevant situation
-2target BER, we calculate the SNR threshold value.Figure 35 has drawn the SNR threshold value for the function as AS of the different value of user's average A OA.For low user's angular distance, the reliable transmission with rational SNR demand (being 18dB) is only possible for take the channel that high AS is feature.On the other hand, when the user spatially separates, need less SNR to meet identical target BER.
Figure 36 shows the SNR threshold value for 5 users' situation.Generate user's average A OA of the value with different angular distance Δ φ according to the definition in (13).We observe for Δ φ=0 ° and AS<15 °, and due to the little angular distance between the user, the BD poor performance, do not meet target BER.For the AS increased, the SNR demand that meets fixing target BER reduces.On the other hand, for Δ φ=30 °, at low AS, obtain minimum SNR demand, consistent with the result in Figure 35.Along with AS increases, the SNR threshold value is saturated in the independent same distribution channel.Note having 5 users' Δ φ=30 ° of AOA scopes corresponding to [60 °, 60 °], this is typical for the base station in the cellular system with 120 ° of sector elements.
Next, we have studied the performance of the ASel delivery plan in spatial correlation channel.Figure 37 has compared the SNR threshold value for the BD with 1 and 2 additional antenna and the ASel of two user situations.We have considered two kinds of different situations of the angular distance between the user: { AOA1=0 °, AOA2=0 ° } and { AOA1=0 °, AOA2=90 ° }.Be used for the curve of BD scheme (there is no a day line options) with identical at Figure 35.We observe ASel and have produced respectively the SNR gain of 8dB with 1 and 2 additional antenna and 10dB for high AS.Along with AS reduces, the gain due to ASel on BD is because the quantity minimizing of the degree of freedom in the MIMO broadcast channel becomes less.What is interesting is, for AS=0 ° (close to the LOS channel) and situation { AOA1=0 °, AOA2=90 ° }, ASel does not provide any gain due to the difference in spatial domain.Figure 38 shows the result similar to Figure 37, but for 5 users' situation.
We have calculated as the SNR threshold value of the function of the number of users (M) in system and (have supposed 10 for BD and ASel delivery plan
-2general objectives BER).The SNR threshold value is corresponding to average SNR, so that total transmitting power is constant for any M.We suppose at azimuth coverage [φ
m, φ
m]=[-60 °, 60 °] in largest interval between the average A OA of each customer group.Then, the angular distance between the user is Δ φ=120 °/(M-1).
Figure 39 shows the SNR threshold value for the BD scheme with different AS values.We observe due to the large angular distance between the user, and AS=0.1 ° (i.e. low angular spread) for the user with less quantity (being K≤20), obtain minimum SNR demand.Yet, for M > and 50, because Δ φ is very little and BD can not carry out, the SNR demand is far longer than 40dB.In addition, for AS > 10 °, the SNR threshold value almost keeps constant for any M, and the DIDO system in spatial correlation channel approaches the performance of independent same distribution channel.
For the value that reduces the SNR threshold value the performance of improving the DIDO system, we apply the ASel delivery plan.Figure 40 shows the SNR threshold value in having the spatial correlation channel of AS=0.1 ° for the BD with 1 and 2 additional antenna and ASel.For reference, we have also reported the curve for independent same distribution situation shown in Figure 32.Can see, for less user (being M≤10), owing in the DIDO broadcast channel, lacking diversity, a day line options does not help to reduce the SNR demand.Along with number of users increases, ASel is benefited from multi-user diversity, has produced SNR gain (being 4dB for M=20).In addition, for M≤20, the performance of the ASel with 1 or 2 additional antenna in high spatial correlation channel is identical.
Then we calculate the SNR threshold value for two kinds of other channel conditions: the AS=10 ° in the AS=5 in Figure 41 ° and Figure 42.Figure 41 compares with Figure 40, shows due to larger angular spread, and ASel has produced also for the relatively user's of small number (being M≤10) SNR gain.As reported in Figure 42, for AS=10 °, the SNR threshold value further reduces, because the gain of ASel becomes higher.
Finally, we have summed up the result proposed for correlated channels at present.Figure 43 and Figure 44 show the conduct that has respectively 1 and 2 the additional antenna SNR threshold value for the function of the number of users (M) of BD and ASel scheme and angular spread (AS).Note, the situation of AS=30 ° is in fact corresponding to the independent same distribution channel, and we use this value of AS for diagrammatic representation in the drawings.We observe, although BD is affected by channel space-related, ASel has produced the almost identical performance for any AS.In addition, for AS=0.1 °, due to multi-user diversity, ASel is similar to the BD performance for low M, and surpasses BD for large M (being M >=20).
Figure 49 has compared the performance of DIDO schemes different aspect the SNR threshold value.The DIDO scheme of considering is: BD, ASel, the BD with feature mode selection (BD-ESel) and high specific merge (MRC).Notice that MRC does not eliminate the interference (unlike other method) at the transmitter place in advance, but in the situation that the user is separated the gain that provides larger by space.In Figure 49, we have drawn when two users lay respectively at the side of emission array and have penetrated direction while becoming-30 ° and 30 °, for DIDO N * 2 systems for target BER=10
-2the SNR threshold value.We observe, and for low AS, the MRC scheme compares with other scheme the gain that 3dB is provided, because user's space channel is separated well, the impact of the interference between the user is very little.Note, the gain of the MRC on DIDO N * 2 is due to array gain.For the AS that is greater than 20 °, the QR-ASel scheme surpasses other scheme and compares with the selectable BD2 of tool * 2 not the gain that has produced about 10dB.QR-ASel and BD-ESel provide about identical performance for the arbitrary value of AS.
Above-described is new self adaptation transmission technology for the DIDO system.The method dynamic translation between the DIDO sending mode strengthens the throughput for fixing target error rate to different users.The performance of the DIDO system of different stage is measured under different propagation conditions, and the huge gain of observing in throughput can realize as DIDO pattern and the number of users of the function of propagation condition by Dynamic Selection.
III. the precompensation of frequency and phase difference
a. background
As described above, wireless communication system carrys out transmission information with carrier wave.These carrier waves are normally sinusoidal wave, and its amplitude and/or phase response are in the information be sent out and modulated.Sinusoidal wave nominal frequency is known as carrier frequency.In order to create this waveform, transmitter synthesizes one or two sine wave, and creates the signal after the modulation overlapped on the sine wave with designated carrier frequency by up-conversion.This can realize by direct conversion, and wherein, signal is directly modulated on carrier wave or by a plurality of up-conversion stage.In order to process this waveform, the necessary received RF signal of demodulation of receiver, and effectively remove modulated carrier.This needs the synthetic one or more sinusoidal signals of receiver to be reversed in the modulated process at transmitter place, is known as the frequency reducing conversion.Regrettably, the sine wave signal generated at transmitter and receiver obtains from different reference oscillators.The frequency reference of perfect (perfect) that do not had reference oscillator to create; In fact, usually and actual frequency some deviations are arranged.
In wireless communication system, in the difference of the output of the reference oscillator at transmitter and receiver place, created the phenomenon that is known as carrier frequency shift or simple frequency shift (FS) at the receiver place.In essence, after the frequency reducing conversion, some residue modulation (corresponding to the difference in the sending and receiving carrier wave) are arranged in received signal.The distortion that this has created in received signal, caused higher bit error rate and lower throughput.
Existence is for the treatment of the different technologies of carrier frequency shift.Most methods is estimated the carrier frequency shift at the receiver place, then applies the offset correction of carrier frequency algorithm.It is blindness (blind) that the Carrier frequency offset estimation algorithm is used following methods: offset-QAM (T.Fusco and M.Tanda, " Blind Frequency-offset Estimation for OFDM/OQAM Systems; " Signal Processing, IEEE Transactions on[is also referring to Acoustics, Speech, and Signal Processing, IEEE Transactions on], vol.55, pp.1828-1838,2007); Cyclophysis (E.Serpedin, A.Chevreuil, G. B.Giannakis and P. Loubaton, " Blind channel and carrier frequency offset estimation using periodic modulation precoders; " Signal Processing, IEEE Transactions on[is also referring to Acoustics, Speech, and Signal Processing, IEEE Transactions on], vol.48, no.8, pp.2389-2405, Aug.2000); Perhaps Cyclic Prefix (the J.J.van de Beek in OFDM (OFDM) structural approach, M.Sandell and P. O.Borjesson, " ML estimation of time and frequency offset in OFDM systems, " Signal Processing, IEEE Transactions on[is also referring to Acoustics, Speech, and Signal Processing, IEEE Transactions on], vol.45, no.7, pp.1800-1805, July1997; U.Tureli, H.Liu and M.D.Zoltowski, " OFDM blind carrier offset estimation:ESPRIT, " IEEE Trans.Commun., vol.48, no.9, pp.1459-1461, Sept.2000; M.Luise, M.Marselli and R.Reggiannini, " Low-complexity blind carrier frequency recovery for OFDM signals over frequency-selective radio channels; " IEEE Trans.Commun., vol.50, no.7, pp.1182-1188, July2002).
Replacedly, special-purpose training signal can be utilized, data symbol (the P. H.Moose that comprises repetition, " A technique for orthogonal frequency division multiplexing frequency offset correction; " IEEE Trans.Commun., vol.42, no.10, pp.2908-2914, Oct.1994); Two different symbols (T.M.Schmidl and D.C.Cox, " Robust frequency and timing synchronization for OFDM, " IEEE Trans.Commun., vol.45, no.12, pp.1613-1621, Dec.1997); Known symbol sebolic addressing (M.Luise and R.Reggiannini, " the Carrier frequency acquisition and tracking for OFDM systems perhaps periodically inserted, " IEEE Trans.Commun., vol.44, no.11, pp.1590-1598, Nov.1996).Correction can occur in the analog or digital mode.The signal that receiver can also come precorrection to send by Carrier frequency offset estimation is to eliminate skew.Due to multicarrier and the ofdm system sensitivity to frequency shift (FS), offset correction of carrier frequency is extensively studied (J.J.van de Beek for multicarrier and ofdm system, M.Sandell and P. O.Borjesson, " ML estimation of time and frequency offset in OFDM systems; " Signal Processing, IEEE Transactions on[is also referring to Acoustics, Speech, and Signal Processing, IEEE Transactions on], vol.45, no.7, pp.1800-1805, July1997; U.Tureli, H.Liu and M.D.Zoltowski, " OFDM blind carrier offset estimation:ESPRIT, " IEEE Trans.Commun., vol.48, no.9, pp.1459-1461, Sept.2000; T.M.Schmidl and D.C.Cox, " Robust frequency and timing synchronization for OFDM, " IEEE Trans.Commun., vol.45, no.12, pp.1613-1621, Dec.1997; M.Luise, M.Marselli and R.Reggiannini, " Low-complexity blind carrier frequency recovery for OFDM signals over frequency-selective radio channels; " IEEE Trans.Commun., vol.50, no.7, pp.1182-1188, July2002).
Frequency offset estimation and proofread and correct for multiple antenna communication or more generally MIMO (multiple-input and multiple-output) system be important problem.In mimo system, transmitting antenna is locked into a frequency reference, and receiver is locked into another frequency reference, and single skew is arranged between transmitter and receiver.Having proposed several algorithms uses training signal to process this problem (K.Lee and J.Chun, " Frequency-offset estimation for MIMO and OFDM systems using orthogonal training sequences; " IEEE Trans.Veh.Technol., vol.56, no.1, pp.146-156, Jan.2007; M.Ghogho and A.Swami, " Training design for multipath channel and frequency offset estimation in MIMO systems; " Signal Processing, IEEE Transactions on[is also referring to Acoustics, Speech, and Signal Processing, IEEE Transactions on], vol.54, no.10, pp.3957-3965, Oct.2006; And adaptive tracking C.Oberli and B.Daneshrad, " Maximum likelihood tracking algorithms for MIMOOFDM; " in Communications, 2004IEEE International Conference on, vol.4, June20-24,2004, pp.2468-2472).Run into prior problem in mimo system, wherein, transmitting antenna is not locked into same frequency reference, but reception antenna is locked into together.In fact this occur in the up link of space division multiple access access (SDMA) system, and the SDMA system is regarded as mimo system, and wherein different user is corresponding to different transmitting antennas.In this case, the compensation of frequency shift (FS) is more complicated.Particularly, frequency shift (FS) has created the interference in the different MIMO be sent out stream.Can be with estimating combining of complexity and equalization algorithm is proofreaied and correct (A.Kannan, T.P. Krauss and M.D.Zoltowski, " Separation of cochannel signals under imperfect timing and carrier synchronization, " IEEE Trans.Veh.Technol., vol.50, no.1, pp.79-96, Jan.2001), and the equilibrium after Frequency offset estimation (T.Tang and R.W.Heath, " Joint frequency offset estimation and interference cancellation for MIMO-OFDM systems[mobile radio], " 2004.VTC2004-Fall.2004IEEE60
thvehicular Technology Conference, vol.3, pp.1553-1557, Sept.26-29,2004, X.Dai, " Carrier frequency offset estimation for OFDM/SDMA systems using consecutive pilots, " IEEE Proceedings-Communications, vol.152, pp.624-632, Oct.7,2005).A few thing has been processed the relevant issues of excess phase shift and tracking error, wherein excess phase shift is estimated and is compensated after Frequency offset estimation, but up link (the L Haring of SDMAOFDMA system has only been considered in this work, S.Bieder and A.Czylwik, " Residual carrier and sampling frequency synchronization in multiuser OFDM systems; " 2006.VTC2006-Spring.IEEE63rd Vehicular Technology Conference, vol.4, pp.1937-1941,2006).When transmitting and receiving antenna and thering is different frequency references, the most serious situation occurs in mimo system when all.Asymptotic analysis (O.Besson and the P.Stoica of the evaluated error in the flat fading channel have only been processed about the only available work of this topic, " On parameter estimation of MIMO flat-fading channels with frequency offsets; " Signal Processing, IEEE Transactions on[is also referring to Acoustics, Speech, and Signal Processing, IEEE Transactions on], vol.51, no.3, pp.602-613, Mar.2003).
When the different transmit antennas of mimo system does not have identical frequency reference, and reception antenna is independently during processing signals, and situation about having been furtherd investigate occurs.This occurs in to be known as in distributed input and output (DIDO) communication system (in the literature also referred to as the MIMO broadcast channel) and occurs.The DIDO system comprises the access point with spaced antenna, described antenna sends data streams in parallel (via precoding) and strengthens the throughput of down link to a plurality of users, now uses identical Radio Resource (being identical time slot duration and frequency band) as conventional SISO system.The DIDO system be described in detail in S.G.Perlman and T.Cotter, in the U.S. Patent application 20060023803 that is entitled as " System and method for distributed input-distributed output wireless communications " of submitting in July, 2004, propose.The mode that many enforcement DIDO precoders are arranged.A solution is block diagonalization (BD), in for example with Publication about Document, describe: Q.H.Spencer, A.L.Swindlehurst and M.Haardt, " Zero-forcing methods for downlink spatial multiplexing in multiuser MIMO channels; " IEEE Trans.Sig.Proc, vol.52, pp.461-471, Feb.2004; K.K.Wong, R.D.Murch and K.B.Letaief, " A joint-channel diagonalization for multiuser MIMO antenna systems, " IEEE Trans.Wireless Comm., vol.2, pp.773-786, JuI2003; L.U.Choi and R.D.Murch, " A transmit preprocessing technique for multiuser MIMO systems using a decomposition approach, " IEEE Trans.Wireless Comm., vol.3, pp.20-24, Jan2004; Z.Shen, J.G.Andrews, R.W.Heath and B.L Evans, " Low complexity user selection algorithms for multiuser MIMO systems with block diagonalization; " be accepted and be published in IEEE Trans.Sig.Proc, Sep.2005; Z.Shen, R.Chen, J.G.Andrews, R.W.Heath and B.L Evans, " Sum capacity of multiuser MIMO broadcast channels with block diagonalization, " be submitted to IEEE Trans.Wireless Comm., Oct.2005; R.Chen, R.W.Heath and J.G.Andrews, " Transmit selection diversity for unitary precoded multiuser spatial multiplexing systems with linear receivers; " be accepted the Trans to IEEE, on Signal Processing, 2005.
In the DIDO system, send precoding and be used to separate the data flow for different user.When the transmitting antenna rf chain is not shared same frequency reference, carrier frequency shift has caused the several problems relevant to System Implementation.When this occurs, each antenna effectively sends with slightly different carrier frequency.The integrality that this has destroyed the DIDO precoder, cause each user to suffer extra interference.What below propose is several solutions to this problem.In an execution mode of solution, the DIDO transmitting antenna is shared a frequency reference by wired, optics or wireless network.In another execution mode of solution, one or more user's estimated frequency offset differences (antenna between skew in relative different) and this information is sent it back to transmitter.Then transmitter precorrection frequency shift (FS) proceed to estimate phase place for the training of DIDO and precoder.This execution mode has problem when there is delay in feedback channel.Reason is that the residual phase error created by trimming process possible be arranged, and this trimming process is not considered channel estimating subsequently.In order to address this problem, an other execution mode is used new frequency shift (FS) and phase estimating device, by estimated delay, has solved this problem.Provide result based on emulation with by the actual measurement that the DIDO-OFDM prototype is carried out.
The frequency proposed in this document and phase deviation compensation method may be sensitiveer to the evaluated error of the noise due to the receiver place.Therefore, another execution mode has proposed the method for estimating for the time and frequency shift, also very strong under low SNR condition.
The different methods for time of implementation and Frequency offset estimation is arranged.Due to its sensitivity to synchronous error, the many methods in these methods propose for the OFDM waveform specially.
These algorithms are not typically used the structure of OFDM waveform, for single carrier wave and multicarrier waveform, are therefore generally enough.The algorithm the following describes use known fiducial mark (for example, training data) with the class of assisting synchronous technology among.Many methods are that the expansion of the frequency offset estimator of Moose (is shown in P.H.Moose, " A technique for orthogonal frequency division multiplexing frequency offset correction; " IEEE Trans.Commun., vol.42, no.10, pp.2908-2914, Oct.1994).Moose has proposed with the training signal of two repetitions and has used the phase difference between received signal to obtain frequency shift (FS).The method of Moose only can be proofreaied and correct mark (fractional) frequency shift (FS).The expansion of the method for Moose proposes (T.M.Schmidl and D.C.Cox, " Robust frequency and timing synchronization for OFDM, " IEEE Trans.Commun. by Schmidl and Cox, vol.45, no.12, pp.1613-1621, Dec.1997).Their main innovation is to use the OFDM symbol of one-period and the training symbol of other differential coding.The integer offset correction that differential coding in second symbol is realized.Coulson has considered at T.M.Schmidl and D.C.Cox, " Robust frequency and timing synchronization for OFDM, " IEEE Trans.Commun., vol.45, no.12, pp.1613-1621, the similar setting of describing in Dec.1997, and at A.J.Coulson, " Maximum likelihood synchronization for OFDM using a pilot symbol:analysis, " IEEE J.Select.Areas Commun., vol.19, no.12, pp.2495-2503, Dec.2001 and A.J.Coulson, " Maximum likelihood synchronization for OFDM using a pilot symbol:algorithms, " IEEE J.Select.Areas Commun., vol.19, no.12, pp.2486-2494, the detailed discussion of algorithm and analysis is provided in Dec.2001.A main difference is the correlation properties that Coulson has used the maximal-length sequence of repetition to provide.He also advises using linear frequency modulation (chirp) signal, because its constant envelope properties in time domain and frequency domain.Coulson has considered actual details but has not comprised the integer estimation.The training signal of a plurality of repetitions is by Minn et.al.in H.Minn, V.K.Bhargava and K.B.Letaief, " A robust timing and frequency synchronization for OFDM systems; " IEEE Trans.Wireless Commun., vol.2, no.4, pp.822-839, July2003 considers, but the structure of training does not have optimised.Shi and Serpedin have proposed some optimalitys (K.Shi and E.Serpedin that training structure has the idea that forms frame synchronization, " Coarse frame and carrier synchronization of OFDM systems:a new metric and comparison; " IEEE Trans.Wireless Commun., vol.3, no.4, pp.1271-1284, July2004).An embodiment of the invention have used the method for Shi and Serpedin to carry out frame synchronization and fractional frequency bias estimation.
Many methods in the literature concentrate on frame synchronization and fractional frequency offset correction.The integer offset correction is used at T.M.Schmidl and D.C.Cox, " Robust frequency and timing synchronization for OFDM, " IEEE Trans.Commun., vol.45, no.12, pp.1613-1621, the other training symbol in Dec.1997 is solved.For example, Morrelli etc. are at M.Morelli, A.N.D ' Andrea and U.Mengali, " Frequency ambiguity resolution in OFDM systems, " IEEE Commun.Lett., vol.4, no.4, pp.134-136, obtained T.M.Schmidl and D.C.Cox in Apr.2000, " Robust frequency and timing synchronization for OFDM; " IEEE Trans.Commun., vol.45, no.12, pp.1613-1621, the improvement version of Dec.1997.Use the interchangeable method of different preamble structures to propose (M.Morelli and U.Mengali by Morelli and Mengali, " An improved frequency offset estimator for OFDM applications; " IEEE Commun.Lett., vol.3, no.3, pp.75-77, Mar.1999).This method has used the correlation between M the identical training symbol repeated to increase by the M factor scope of fractional frequency offset estimator.This is best linear unbias estimator and has accepted maximum skew (having suitable design), but the timing synchronization do not provided.
system is described
An embodiment of the invention use the precoding based on channel condition information to eliminate frequency and the phase deviation in the DIDO system.See Figure 11 and for the top associated description of the description of this execution mode.
In an embodiment of the invention, each user uses the receiver that is equipped with frequency offset estimator/compensator.Go out as shown in Figure 45, in an embodiment of the invention, the system that comprises receiver comprises a plurality of RF unit 4508, corresponding a plurality of A/D unit 4510, the receiver that is equipped with frequency offset estimator/compensator 4512 and DIDO feedback maker unit 4506.
description to an execution mode of the algorithm for DIDO2 * 2 situations
What the following describes is the execution mode for the algorithm of the frequency/phase migration of DIDO system.The DIDO system model starts in the situation that have and do not have frequency/phase skew and be described.For easy, provide the particular implementation of DIDO2 * 2 systems.Yet basic principle of the present invention can also be implemented in high-order DIDO system.
there is/do not have the DIDO system model of frequency and phase deviation
The received signal of DIDO2 * 2 can be write as for first user:
r
1[t]=h
11(w
11x
1[t]+w
21x
2[t])+h
12(w
12x
1[t]+w
22x
2[t]) (1)
And write as for second user:
r
2[t]=h
21(w
11x
1[t]+w
21x
2[t])+h
22(w
12x
1[t]+w
22x
2[t]) (2)
Wherein t is the discrete time index, h
mnand W
mnrespectively channel and the DIDO precoding weight between m user and n transmitting antenna, x
mit is the transmitted signal for user m.Note h
mnand w
mnnot the function of t, because we suppose that channel is constant on the cycle between training and data transmission.
When frequency and phase deviation exist, the signal received is represented as
And
Wherein, T
sthe is-symbol cycle; For n transmitting antenna, ω
tn=2 Π f
tn; For m user, ω
um=2 Π f
um; And f
tnand f
umit is respectively the practical carrier frequency (by bias effect) for n transmitting antenna and m user.Value t
mnbe illustrated in channel h
mnon cause the random delay of phase deviation.Figure 46 has drawn DIDO2 * 2 system models.
For the time, we use to give a definition:
Δω
mn=ω
Um-ω
Tn (5)
To be used for being illustrated in the frequency shift (FS) between m user and n transmitting antenna.
the description of an embodiment of the invention
According to the method for an embodiment of the invention, in Figure 47, be illustrated.The method comprises that following general step (comprises sub-step, as shown): for the cycle of training 4701 of Frequency offset estimation; For the cycle of training 4702 of channel estimating; Data via the balanced DIDO precoding of tool send 4703.These steps are described in detail in the following.
(a) for the cycle of training (4701) of Frequency offset estimation
During the first cycle of training, base station will send to from one or more training signals of each transmitting antenna one (4701a) in the user.As described here, " user " is wireless client device.For the situation of DIDO2 * 2, the signal received by m user is provided by following:
Wherein, p
1and p
2it is respectively the training sequence sent from the first and second antennas.
M user can use the frequency offset estimator (by the convolution of training sequence) of any type and estimate shifted by delta ω
m1with Δ ω
m2.Then, according to these values, the user calculates two frequency shift (FS)s between transmitting antenna:
Δω
T=Δω
m2-Δω
m1=ω
T1-ω
T2 (7)
Finally, the value in (7) is fed back to base station (4701b).
Note the p in (6)
1and p
2being designed to is quadrature, thereby the user can estimate Δ ω
m1with Δ ω
m2.Replacedly, in one embodiment, identical training sequence is used in two continuous time slots, and the user therefrom estimates skew.In addition, in order to improve the estimation of the skew in (7), above-described identical calculating can be done for all users (not only for m user) of DIDO system, and last estimation can be (the weighting) mean value from the value of all users' acquisitions.Yet this solution needs more computing time and feedback quantity.Finally, the renewal of Frequency offset estimation only just needs when the frequency shift (FS) temporal evolution.Therefore, according to the stability of the clock at transmitter place, the step 4701 of algorithm can be performed (sending for each data) for a long time, makes above-mentioned feedback reduce.
(b) for the cycle of training (4702) of channel estimating
During the second cycle of training, at first base station maybe must have the frequency shift (FS) feedback of the value (7) from m user or from a plurality of users.Value in (7) is used to the frequency shift (FS) of precompensation at transmitting terminal.Then, base station sends to all users by training data and comes for channel estimating (4702a).
For DIDO2 * 2 systems, the signal received at first user place is provided by following:
And second user place:
Wherein,
and Δ t is the random or known delay between first transmission and second of base station sends.In addition, p
1and p
2it is respectively the training sequence sent from the first and second antennas of user's frequency shift (FS) and channel estimating.
Note, precompensation only is applied to the second antenna in this embodiment.
Launch (8), we obtain
Similarly for the second user:
Wherein,
At receiving terminal, the user is by using training sequence p
1and p
2carry out compensating frequency offset residue.Then, the user is estimated (4702b) by the trained vector channel:
These channels in (12) or channel condition information (CSI) are fed back to base station (4702b), and the DIDO precoder is calculated in base station as described in lower part.
(c) there is the DIDO precoding (4703) of precompensation
Base station receives the channel condition information (CSI) (12) and calculates the weight (4703a) of precoding by block diagonalization (BD) from the user, so that
Wherein, vector h
1in (12), be defined, and w
m=[w
m1, w
m2].Note, the present invention who proposes in the disclosure can be used in any other DIDO method for precoding except BD.Base station is also by using the estimation in (7) to carry out the precompensation frequency shift (FS), and delay (the Δ t trained between transmission and current transmission by estimation second
0) carry out precompensation phase deviation (4703a).Finally, base station sends to user (4703b) via the DIDO precoder by data.
After process of transmitting, the signal received at user 1 place is provided by following:
Similarly, for user 2, we obtain:
Launch (16):
Wherein,
Finally, the user calculates frequency offset residue and channel estimating is carried out demodulated data stream x
1[t] and x
2[t] (4703c).
be generalized to DIDON * M
In this part, the technology of before describing is generalized to the DIDO system with N transmitting antenna and M user.
i. the cycle of training of user's Frequency offset estimation
During the first cycle of training, because the signal received by m user of the training sequence sent from N antenna is provided by following:
Wherein, p
nit is the training sequence sent from n antenna.
Estimating shifted by delta ω
mnafterwards,
m user calculates the frequency shift (FS) between first and n transmitting antenna:
Δω
T,1n=Δω
mn-Δω
m1=ω
T1-ω
Tn (19)
Finally, the value in (19) is fed back to base station.
ii. for the cycle of training of channel estimating
During the second cycle of training, at first base station obtains the frequency shift (FS) feedback with the value (19) from m user or from a plurality of users.Value in (19) is used to the frequency shift (FS) of precompensation at transmitting terminal.Then, base station sends to all users by training data and comes for channel estimating.
For DIDO N * M system, the signal received at m user place is provided by following:
Wherein,
And Δ t is the random or known delay between first and second of base station sends.In addition, P
nit is the training sequence sent from n antenna for frequency shift (FS) and channel estimating.
At receiver side, the user is by using training sequence P
ncarry out compensating frequency offset residue.Then, each user m is estimated by the trained vector channel:
And feeding back to base station, the DIDO precoder is calculated in base station as described in following part.
iii. the DIDO precoding that there is precompensation
Base station receives the channel condition information (CSI) (12) and calculates the weight of precoding by block diagonalization (BD) from the user, so that
Wherein, vector h
min (21), be defined, and w
m=[w
m1, w
m2..., w
mN].Base station is also by using the estimation in (19) to carry out the precompensation frequency shift (FS), and delay (the Δ t trained between transmission and current transmission by estimation second
0) carry out precompensation phase deviation.Finally, base station sends to the user via the DIDO precoder by data.
After process of transmitting, the signal received at user i place is provided by following:
Wherein,
use attribute (22), we obtain:
Finally, the user calculates frequency offset residue and channel estimating is carried out demodulated data stream x
i[t].
result
Figure 48 shows the SER result of the DIDO2 that has and do not have frequency shift (FS) * 2 systems.Can see, the method proposed has been eliminated the frequency/phase skew fully, has produced the SER identical with the system that does not have skew.
Next, we assess the sensitivity of proposed compensation method for the fluctuation of frequency offset error and/or real-time skew.Therefore, we are rewritten as (14):
Wherein, ε means evaluated error and/or the variation of the frequency shift (FS) between training and data transmission.Note, the effect of ε is the orthogonal property destroyed in (13), so that the distracter in (14) and (16) is not eliminated fully in advance at the transmitter place.Because like this, the SER performance reduces along with the ε value increased.
Figure 48 shows the SER performance for the frequency offset compensation method of different ∈ values.These result hypothesis T
s=0.3ms (signal that there is the 3KHz bandwidth).We observe, and for ε=0.001Hz (or still less), the SER performance is similar to the situation that there is no skew.
the description of an execution mode of the algorithm of f. estimating for the time and frequency shift
Below, we describe the other execution mode (4701b in Figure 47) of time of implementation and Frequency offset estimation.The structure that transmits of considering is at H.Minn, V.K.Bhargava and K.B.Letaief, " A robust timing and frequency synchronization for OFDM systems, " IEEE Trans.Wireless Commun., vol.2, no.4, pp.822-839, in July2003, propose, at K.Shi and E.Serpedin, " Coarse frame and carrier synchronization of OFDM systems:a new metric and comparison, " IEEE Trans.Wireless Commun., vol.3, no.4, pp.1271-1284, in July2004, studied in great detail.The sequence of the association attributes usually had is used to training.For example, for our system, the Chu sequence is used, the Chu sequence is as at D.Chu, " Polyphase codes with good periodic correlation properties (corresp.), " IEEE Trans.Inform.Theory, vol.18, no.4, pp.531-532, be described in July1972.These sequences have interesting attribute, and they have perfect circular correlation.Allow L
cpthe length that means Cyclic Prefix, N
tthe length that means the component training sequence.Make N
t=M
t, M wherein
tthe length of training sequence.Under these hypothesis, the symbol sebolic addressing for the beginning sent can be write as:
S[n]=t[n-N
t] for n=-1 ... ,-L
cp
S[n]=t[n] for n=0 ..., N
t-1
S[n]=t[n-N
t] for n=N
t..., 2N
t-1
S[n]=-t[n-2N
t] for n=2N
t..., 3N
t-1
S[n]=t[n-3N
t] for n=3N
t..., 4N
t-1
The structure of noting this training signal can be expanded to other length, but has repeated block structure.For example, in order to use 16 training signals, we consider a kind of structure, for example:
[CP,B,B,-B,B,B,B,-B,B,-B,-B,B,-B,B,B,-B,B,]。
By using this structure, and make N
t=4M
t, all algorithms that will describe can be in the situation that do not revise and be used.Effectively, our repetition training sequence.This is particularly useful in the suitable disabled situation of training signal possibility.
After the filtering that symbol rate is mated and down sample, consider following received signal:
Wherein ε is unknown discrete time frequency shift (FS), and Δ is unknown vertical shift, h[1] be unknown discrete time channel coefficients, and v[n] be additional noise.In order to explain the key idea in following part, ignore the existence of additional noise.
I. rough frame synchronization
The purpose of rough frame synchronization is to solve unknown vertical shift Δ.Let us is made giving a definition:
r
1[n]:=[r[n],r[n+1],...,r[n+N
t-1]]
T,
r
2[n]:=[r[n+N
t],r[n+1+N
t],...,r[n+2N
t-1]]
T,
r
3[n]:=[r[n+2N
t],r[n+1+2N
t],...,r[n+3N
t-1]]
T,
r
4[n]:=[r[n+3N
t],r[n+1+3N
t],...,r[n+4N
t-1]]
T,
The rough frame synchronization algorithm proposed is from K.Shi and E.Serpedin, " Coarse frame and carrier synchronization of OFDM systems:a new metric and comparison; " IEEE Trans.Wireless Commun., vol.3, no.4, pp.1271-1284, the algorithm in July2004 takes a hint, and according to maximum-likelihood criterion, obtains.
The improved rough frame synchronization of method 1-: rough frame synchronization estimator has solved following optimization:
Wherein,
Make the signal be corrected be defined as:
Other correction term is used to the little inceptive impulse in compensate for channel and can be conditioned based on application.This extra delay will be included in channel afterwards.
Ii. fractional frequency offset correction
The fractional frequency offset correction is after rough frame synchronization piece.
The improved fractional frequency offset correction of method 2-: the fractional frequency skew is following solution:
This is known as the fractional frequency skew, because algorithm only can correcting offset
This problem will be solved in next part.Allow the fine frequency offset correction signal be defined as:
Note, method 1 and 2 is for the K.Shi preferably that works in frequency selective channel, E.Serpedin, " Coarse frame and carrier synchronization of OFDM systems:a new metric and comparison; " IEEE Trans.Wireless Commun., vol.3, no.4, PP.1271-1284, the improvement of July2004.Here one special innovation be used r recited above and
the estimator of use before having improved because it has been ignored because internal symbol is disturbed the sampling be affected.
Iii. integer frequency deviation is proofreaied and correct
In order to proofread and correct integer frequency deviation, be necessary to write an equivalent system model for signal received after fine frequency offset is proofreaied and correct.The timing error of reservation is absorbed in channel, is not had noisy received signal to there is following structure:
N=0 wherein, 1 ..., 4N
t-1.Integer frequency deviation is k, and unknown equivalent channels is g[l].
The improved integer frequency deviation of method 3-is proofreaied and correct: integer frequency deviation is following solution:
Wherein:
r=D[k]Sg
This has provided the estimation of total frequency shift (FS):
In fact, method 3 has very high complexity.In order to reduce complexity, can make following observation.At first, product S (S*S)
-1s can be by precomputation.Regrettably, this has still stayed sizable matrix multiplication.Adopt alternatively the observation with proposed training sequence, S*S ≈ I.This has produced the method for the support type of following reduction.
The improved integer frequency deviation of method 4-low-complexity is proofreaied and correct:
The integer frequency deviation estimator of low-complexity has solved
Iv. result
In this part, we have compared the performance of the different estimators proposed.
At first, in Figure 50, we have compared the amount of every kind of needed expense of method.Notice that two kinds of new methods have reduced by 10 times to 20 times by expense.For the performance of more different estimators, the MonteCarlo experiment is performed.The setting of considering is that our common NVIS of the linear modulation structure of the symbol rate from having 3K symbol per second sends waveform, and corresponding to the pass band width of 3KHz, and the cosine impulse risen is shaped.For each Monte Carlo, realize, frequency shift (FS) is from [f
max, f
max] on be uniformly distributed and generate.
There is f
maxthe little frequency shift (FS) of=2Hz and do not have the emulation of integer offset correction to be illustrated in Figure 51.Can find out to there is N from this Performance Ratio
t/ M
t=1 performance is slightly demoted from original estimator, although reduced in fact expense.There is N
t/ M
t=4 performance is better, is almost 10dB.Due to the error in the integer bias estimation, all curves have experienced complications at low SNR point.Little error in the integer skew can create large frequency error and large splicing square error.The integer offset correction can be closed to improve performance in little skew.
In the situation that multi-path channel exists, the performance of frequency offset estimator generally reduces.Yet, in Figure 52, close the integer offset estimator and represented extraordinary performance.Therefore, in multi-path channel, the improved fine correction algorithm after the rough correction of carrying out robust is prior.Note, there is N
t/ M
t=4 offset behavior is much better in the multipath situation.
The various steps that propose above embodiments of the present invention can comprise.Described step can realize in the mode of machine-executable instruction, and described instruction makes universal or special processor carry out particular step.For example, the interior various assemblies of described base station/AP and customer set up may be implemented as the software of carrying out on universal or special processor in the above.For fear of the fuzzy parties concerned of the present invention, such as the various known individual calculus thermomechanical components of computer storage, hard disk, input unit etc., from figure, save.
Replacedly, the specialized hardware components (for example application-specific integrated circuit (ASIC) (ASIC)) of the hardwired logic that in one embodiment, shown various functional module and correlation step can be by comprising execution step here or be performed by the combination in any of programmed computer components and custom hardware components.
In one embodiment, allly encode as described above, the particular module of modulation and signal processing logic 903 can be implemented on programmable digital signal processor (DSP) (or DSP group), described DSP is for example used the DSP (for example, TMS320C6000, TMS320C5000 etc.) of the TMS320x framework of Texas Instrument (Texas Instruments).DSP in this embodiment can be embedded in the package card of personal computer, for example, and pci card.Certainly, in the situation that basic principle according to the invention, various DSP framework can be used.
Various parts of the present invention also may be provided in for storing the machine readable media of machine-executable instruction.Machine readable media can include but not limited to flash memory, CD, CD-ROM, DVD ROM, RAM, EPROM, EEPROM, magnetic card or optical card, communication media or be suitable for the machine readable media of other type of store electrons instruction.For example, the present invention can be downloaded as computer program, this computer program can be by being included in carrier wave or other communication media the mode of data-signal for example, for example, from remote computer (server), be sent to requesting computer (for example client) via communication link (, modulator-demodulator or network connect).
Spread all over aforementioned description, for the purpose of explaining, many specific detail are suggested to provide the complete understanding of native system and method.Yet, it will be apparent to one skilled in the art that system and method can in the situation that some in there is no these specific detail be implemented.Therefore, scope of the present invention and essence should be judged according to claims.
In addition, in aforementioned description, many documents are cited to provide of the present invention and more fully understand.All these lists of references of quoting are by reference to being integrated in the application.
Claims (24)
1. one kind for having multiaerial system MAS MU-MAS compensating frequency that multi-user MU sends and the method for phase deviation, and the method comprises:
From each antenna of base station, training signal is sent to or each wireless client device a plurality of wireless client device, in this customer set up one or each customer set up are analyzed each training signal with the generated frequency bias compensation data, and receive described frequency offset compensation data in described base station;
Calculate MU-MAS precoder weight to eliminate in advance the frequency shift (FS) at transmitter place based on described frequency offset compensation data;
Send a plurality of training signals on link between in each antenna of base station and a plurality of wireless client device one or each wireless client device, and analyze each training signal at place, described base station, to obtain the channel characteristics data;
Calculate a plurality of MU-MAS precoder weights based on described channel characteristics data, this MU-MAS precoder weight is calculated the interference of eliminating in advance between frequency and phase deviation and/or user;
By described MU-MAS precoder weight, data are carried out to precoding to generate for the data-signal after the precoding of each antenna of described base station; And
Each antenna by the data-signal after described precoding by described base station sends to each customer set up separately.
2. method according to claim 1, the method also comprises:
Each wireless client device from described a plurality of wireless client device sends to described a plurality of training signals on each antenna of described base station, and each training signal is analyzed to generate the channel characteristics data in this base station.
3. method according to claim 1, the method also comprises:
By described MU-MAS precoder weight, described a plurality of training signals are carried out to precoding to generate for the training signal after the precoding of each antenna of described base station;
From each antenna of described base station, the training signal described precoding is sent to each wireless client device in described a plurality of wireless client device, each customer set up in this customer set up is analyzed each training signal to generate the channel characteristics data, and receives described channel characteristics data in described base station.
4. method according to claim 1, wherein said base station is described wireless client device to be coupled to the access point of wide area network.
5. method according to claim 1, one of them centralized transmitter unit is estimated frequency shift (FS) the described skew of precompensation between all transmitter units, or the antenna of described base station carrys out the shared frequencies benchmark by wired, optics or wireless network.
6. method according to claim 3, wherein carry out the described a plurality of training signals of precoding to reduce feedback overhead for a long time by one or more users.
7. method according to claim 1, wherein said transmitter or receiver are estimated the change rate of described frequency shift (FS) and are determined the turnover rate of training.
8. method according to claim 1, wherein data precoding is used block diagonalization BD technology and is performed.
9. method according to claim 1, wherein said MU-MAS system is distributed input distributed output DIDO communication system, and wherein said MU-MAS precoder weight is DIDO precoder weight.
10. one kind compensates the unbalanced method of inphase quadrature I/Q for the multiaerial system MAS MU-MAS having multi-user MU transmission, and the method comprises:
Send a plurality of training signals on link between in each antenna of base station and a plurality of wireless client device one or each wireless client device, and analyze each training signal in described base station, to obtain the channel characteristics data;
Calculate a plurality of MU-MAS precoder weights based on described channel characteristics data, this MU-MAS precoder weight is calculated eliminates the interference brought due to I/Q gain and unbalance in phase and/or inter-user interference in advance;
By described MU-MAS precoder weight, data are carried out to precoding to generate for the data-signal after the precoding of each antenna of described base station; And
Each antenna by the data-signal after described precoding by described base station sends to each customer set up separately.
11. method according to claim 10, the method also comprises:
Each wireless client device from a plurality of wireless client device sends to described a plurality of training signals on each antenna of described base station, and each training signal is analyzed to generate the channel characteristics data in described base station.
12. method according to claim 10, the method also comprises:
From each antenna of base station, training signal is sent to each wireless client device a plurality of wireless client device, each wireless client device in this customer set up is analyzed each training signal to generate the channel characteristics data, and receives described channel characteristics data in described base station.
13. method according to claim 10, wherein said base station is described wireless client device to be coupled to the access point of wide area network.
14. method according to claim 10, the method also comprises:
With zero, force ZF receiver, least mean-square error MMSE receiver or maximum likelihood ML receiver to come at each user device demodulated data stream to suppress residual interference.
15. method according to claim 10, wherein carry out precoding by block diagonalization BD technology.
16. method according to claim 10, wherein said MU-MAS system is distributed input distributed output DIDO communication system, and wherein said MU-MAS precoder weight is DIDO precoder weight.
17. method according to claim 16, wherein said precoder weight is calculated to eliminate inter-user interference rather than intercarrier interference, and wherein said wireless client device comprises the receiver with the filter for eliminating described ICI.
18. a method that has the communication characteristic of the multiaerial system MAS MU-MAS that multi-user MU sends for dynamically adapting, the method comprises:
Send a plurality of training signals on link between in each antenna of base station and a plurality of wireless client device one or each wireless client device, and analyze each training signal at place, described base station, to obtain the channel characteristics data;
By described channel characteristics data, determine for the instantaneous of described wireless client device or statistical channel quality, i.e. link quality metric;
Determine user's subset and MU-MAS sending mode based on described link quality metric;
Calculate a plurality of MU-MAS precoder weights based on described channel characteristics data;
By described MU-MAS precoder weight, data are carried out to precoding to generate for the data-signal after the precoding of each antenna of described base station; And
Each antenna by the data-signal after described precoding by described base station sends to each customer set up separately in selected subset.
19. method according to claim 18, the method comprises:
To send to from described a plurality of training signals of each wireless client device in described a plurality of wireless client device each antenna of described base station, each training signal is analyzed to generate the channel characteristics data in described base station.
20. method according to claim 18, the method comprises:
From each antenna of base station, training signal is sent to each wireless client device a plurality of wireless client device, each customer set up in this customer set up is analyzed each training signal to generate the channel characteristics data, and receives described channel characteristics data at place, described base station.
21. method according to claim 18, wherein said MU-MAS sending mode comprises the various combination of day line options/diversity or multiplexing, modulation/coding scheme MCS and array configurations/geometry.
22. method according to claim 18, wherein said link quality metric is estimated in time domain, frequency domain and/or spatial domain.
23. method according to claim 18, wherein said link quality metric is included in the signal to noise ratio snr of the signal that described customer set up place receives.
24. method according to claim 18, wherein said MU-MAS system is distributed input distributed output DIDO communication system, wherein said MU-MAS sending mode is based on the DIDO sending mode of described link quality metric, and wherein said MU-MAS precoder weight is DIDO precoder weight.
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RU2016107617A3 (en) | 2019-06-25 |
CN103036839B (en) | 2015-09-30 |
JP2015111849A (en) | 2015-06-18 |
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RU2011131822A (en) | 2013-02-10 |
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RU2578206C2 (en) | 2016-03-27 |
JP2015216699A (en) | 2015-12-03 |
CN103036839A (en) | 2013-04-10 |
JP2020127215A (en) | 2020-08-20 |
RU2011131821A (en) | 2013-02-10 |
CA3025857C (en) | 2022-10-18 |
KR101598324B1 (en) | 2016-02-26 |
CA3025857A1 (en) | 2009-02-26 |
CN103117975A (en) | 2013-05-22 |
RU2700568C2 (en) | 2019-09-18 |
KR20150018900A (en) | 2015-02-24 |
CN103501193B (en) | 2017-04-12 |
JP6922027B2 (en) | 2021-08-18 |
RU2016107617A (en) | 2017-09-07 |
RU2580324C2 (en) | 2016-04-10 |
JP6055524B2 (en) | 2016-12-27 |
CN103117975B (en) | 2017-05-24 |
KR20160136476A (en) | 2016-11-29 |
KR101805345B1 (en) | 2018-01-10 |
JP2017085589A (en) | 2017-05-18 |
JP2013251915A (en) | 2013-12-12 |
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