CN111277521A - Channel estimation and noise filtering method of single carrier frequency domain equalization system - Google Patents
Channel estimation and noise filtering method of single carrier frequency domain equalization system Download PDFInfo
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Abstract
The invention discloses a channel estimation and noise filtering method of a single carrier frequency domain equalization system. The invention belongs to the technical field of communication, and particularly relates to a method for channel estimation and noise filtering in a single carrier frequency domain equalization system. The method mainly comprises the following steps: a receiving end reads M point pilot frequency data; performing least square estimation on the obtained pilot frequency data to obtain a time domain channel of the pilot frequency signal; splicing the front N-1 point data of the time domain channel to the tail part to form a new N + M-1 point time domain channel, and carrying out maximum energy window sliding search on the new time domain channel to obtain the initial position of a maximum energy window; performing noise estimation by using a channel estimation value outside an energy window, and performing combined noise reduction processing outside an energy window according to noise; and (4) filling zero in the original time domain channel after noise reduction to the length of the useful data to obtain the estimated time domain channel of the useful data. The method of the invention uses the method of maximum energy window search and window inner window outer combined noise reduction, reserves the effective energy path in the channel to the maximum extent, filters the noise path, and has accurate channel estimation and small error.
Description
Technical Field
The invention belongs to the technical field of communication, and particularly relates to a channel estimation and noise filtering method in a single carrier frequency domain equalization system.
Background
The IEEE 802.16a standard released in 2003 establishes an air interface standard of a leased frequency band of 2-11 GHz on the basis of the IEEE 802.16 standard, and specifies an SC-FDE system as one of transmission modes. The single carrier transmission mode in the IEEE 802.16a standard is different from the conventional single carrier transmission, and it transmits a modulated high-rate single carrier signal, and the receiving end implements frequency domain equalization by FFT and IFFT transformation, and actually implements frequency domain analysis on the received signal, and such a system is called a single carrier frequency domain equalization system.
The transmission carrier of the signal is a channel, and the main propagation channel is a wireless channel. Due to its harsh propagation environment, the wireless channel generates inter-symbol interference, which severely distorts the received signal. Due to the characteristics of the wireless channel, the channel has great randomness, so that estimation and prediction of the channel are very necessary.
There is a channel estimation method in the prior art. The signal transmitted by this method consists of a pilot signal and useful data. Firstly, inserting a pilot frequency into a proper position of a transmitting end; then, obtaining the channel information of the inserted pilot frequency position at the receiving end through a channel estimation criterion; finally, on the basis of the obtained channel information, the information of the whole channel can be obtained by interpolation, filtering, etc. Specifically, after estimating the frequency domain channel of the pilot frequency position, the time domain channel impulse response is obtained through fast fourier transform (IFFT). Because the length of the pilot frequency is smaller than that of the useful data, zero padding is sequentially needed to be carried out after the pilot frequency time domain channel impulse response, and the length of the useful signal is padded, so that the time domain channel impulse response of the useful signal is obtained.
The inventor finds that at least the following problems exist in the prior art: in an ideal case, the points with large energy of the time domain channel impulse response obtained through channel estimation are usually all concentrated at the front end of the channel, and the energy value of the point at the tail end of the time domain channel impulse response is generally zero. In the specific implementation process, due to the combined action of the filters at the transmitting end and the receiving end and the multipath channel, the time domain channel impulse response obtained through channel estimation generates an energy diffusion phenomenon, if the accurate channel estimation FFT window position cannot be given in the synchronization stage, due to the cyclic shift generated by FFT calculation, the paths with larger time domain channel energy are obtained and are not necessarily all concentrated at the front end of the channel, and a plurality of paths with larger energy can be generated at the tail end of the time domain channel. In addition, considering the influence of noise, each path of the time domain channel impulse response is doped with noise energy. Aiming at the tail part with larger energy diameter, the prior art mainly comprises the following two types: (1) in the timing synchronization stage, a first energy path meeting the conditions is found by setting a static threshold and is used as an initial point of an FFT window; (2) on the basis of giving the starting point of the FFT window in the synchronization stage, a fixed m-point access is carried out in advance and is taken as a new FFT starting point. The method for doping noise for each path mainly reserves the maximum n paths in a time domain channel, and sets the rest paths to be zero. The wireless channel is dynamically changed, a channel estimation method for setting a static threshold and fixing m-point access in advance and a noise filtering mode for reserving the maximum diameter of n points are not suitable for complicated and variable wireless channel conditions, and the problem that a tail part has a large energy point and the channel noise can not be filtered to the maximum extent. The channel estimation result obtained in this way removes the large energy points that may appear at the tail, and has large errors with the useful data channel condition, and these errors can cause demodulation errors and reduce demodulation performance.
Disclosure of Invention
The invention aims to provide a channel estimation and noise filtering method of a single carrier frequency domain equalization system. The method can fully consider the larger energy point at the tail end of the time domain channel impulse response caused by FFT cyclic shift, circularly shift the larger energy point at the tail end to the front end of the channel by adopting a maximum energy window method, and remove the noise influence by adopting a window external zero and a window internal threshold screening method. The method provided by the invention has accurate channel estimation and small error, and can ensure the stable and reliable performance of the channel in the high-speed service.
The technical scheme of the invention is as follows: a channel estimation and noise filtering method for a single carrier frequency domain equalization system comprises the following steps:
step 1.1, a receiving end of a single carrier frequency domain equalization system reads M-point pilot signals and obtains a time domain channel by using an LS algorithm;
step 1.2, splicing the front N-1 point data of the time domain channel to the tail part thereof to form a new N + M-1 point time domain channel;
step 1.3, carrying out maximum energy window sliding search on the spliced time domain channel, and finding out the position with the maximum signal energy in the window;
step 1.4, noise estimation is carried out according to the data outside the window of the maximum energy window;
step 1.5, carrying out noise filtering processing on the time domain channel, namely carrying out noise filtering on the inner window energy diameter by taking noise as a threshold, and clearing the outer window energy diameter;
and step 1.6, obtaining a frequency domain channel of the useful signal according to the time domain channel after noise filtering.
Further, in step 1.1, the LS algorithm is:
wherein Y is frequency domain data of the received pilot signal, X is frequency domain data of the local pilot signal, and the time domain channel estimation is
Further, in step 1.3, the maximum energy window sliding search method specifically includes:
1.3.1, the window length of the energy window is N, and N is greater than the multipath time delay of a channel;
1.3.2 said energy window sliding search from the kth data h of the new N + M-1 point time domain channelkStarting to calculate, sliding to obtain the energy sum P of continuous N datak：
1.3.3, screening out the maximum energy window and recording the initial position k.
Further, in step 1.4, the noise estimation method specifically includes:
further, in step 1.5, the performing noise reduction processing on the time domain channel includes:
1.5.1, setting zero for each path of the time domain channel outside the maximum energy window;
1.5.2, screening each path of the time domain channel in the maximum energy window by taking the noise power as a threshold, and setting the point in the window which does not pass the noise threshold to be zero.
Further, in step 1.6, the estimating the frequency domain channel of the useful signal includes the steps of:
1.6.1, zero-filling the time domain channel of the M point pilot signal to the length of the useful signal to obtain the estimated time domain channel of the useful signal;
1.6.2, carrying out Fourier transform on the time domain channel of the useful signal to obtain a frequency domain channel of the useful signal.
The invention has the following beneficial effects: the method solves the problem of larger energy points appearing at the end of a time domain channel by using a maximum channel energy window searching method; and removing the influence of noise on a channel by using a method of noise threshold noise filtering in a window and small energy path zero setting outside the window. Compared with the traditional channel estimation algorithm of single carrier frequency domain equalization, the method can fully consider the time-varying property of a wireless channel, circularly shift a larger energy point at the tail end to the front end of the channel by adopting a maximum energy window method, and remove the influence of noise paths by combining a window external zero and a window internal threshold screening method, thereby ensuring that the channel estimation is more accurate, the error is small, and the stable and reliable performance of the channel in high-speed service can be ensured.
Drawings
FIG. 1 is a general flow diagram of the present invention;
FIG. 2 is a diagram illustrating a data framing structure according to an embodiment of the present invention;
FIG. 3 is a diagram illustrating an impulse response of a time domain channel after splicing according to an embodiment of the present invention;
FIG. 4 is a diagram illustrating a comparison of the performance of the channel estimation and noise filtering method in an embodiment of the present invention;
fig. 5 is a diagram illustrating channel parameters used in an embodiment of the invention.
Detailed Description
The technical scheme of the invention is described in detail by combining the examples and the attached drawings of the specification:
a channel estimation and noise filtering method for a single carrier frequency domain equalization system comprises the following steps:
step 1.1, a receiving end of a single carrier frequency domain equalization system reads M-point pilot signals and obtains a time domain channel by using an LS algorithm;
step 1.2, splicing the front N-1 point data of the time domain channel to the tail part thereof to form a new N + M-1 point time domain channel;
step 1.3, carrying out maximum energy window sliding search on the spliced time domain channel, and finding out the position with the maximum signal energy in the window;
step 1.4, noise estimation is carried out according to the data outside the window of the maximum energy window;
step 1.5, carrying out noise filtering processing on the time domain channel, namely carrying out noise filtering on the inner window energy diameter by taking noise as a threshold, and clearing the outer window energy diameter;
and step 1.6, obtaining a frequency domain channel of the useful signal according to the time domain channel after noise filtering.
Further, in step 1.1, the LS algorithm is:
wherein Y is frequency domain data of the received pilot signal, X is frequency domain data of the local pilot signal, and the time domain channel estimation is
Further, in step 1.3, the maximum energy window sliding search method specifically includes:
1.3.1, the window length of the energy window is N, and N is greater than the multipath time delay of a channel;
1.3.2 said energy window sliding search from the kth data h of the new N + M-1 point time domain channelkStarting to calculate, sliding to obtain the energy sum P of continuous N datak：
1.3.3, screening out the maximum energy window and recording the initial position k.
Further, in step 1.4, the noise estimation method specifically includes:
further, in step 1.5, the performing noise reduction processing on the time domain channel includes:
1.5.1, setting zero for each path of the time domain channel outside the maximum energy window;
1.5.2, screening each path of the time domain channel in the maximum energy window by taking the noise power as a threshold, and setting the point in the window which does not pass the noise threshold to be zero.
Further, in step 1.6, the estimating the frequency domain channel of the useful signal includes the steps of:
1.6.1, zero-filling the time domain channel of the M point pilot signal to the length of the useful signal to obtain the estimated time domain channel of the useful signal;
1.6.2, carrying out Fourier transform on the time domain channel of the useful signal to obtain a frequency domain channel of the useful signal.
Referring to fig. 1, the channel estimation and noise filtering method of the present invention mainly includes a data reading unit, an LS channel estimation unit, a maximum energy window search, a noise reduction process, and a frequency domain channel for calculating a useful channel;
the method adopts a mode of searching a maximum energy window to fully consider a larger energy point at the end of a channel, and eliminates the influence of noise by a method of jointly filtering noise outside and inside the window, so that the obtained channel is accurate in estimation and small in error, and the stable and reliable performance of the channel in high-speed service can be ensured. The method mainly comprises the following steps:
data reading: performing pilot frequency data reading on the received time domain data, and taking the data reading position in advance of M points to obtain pilot frequency data UW required by an LS channel estimation unitsig。
As shown in fig. 2, the time domain Data is mainly composed of a pilot signal (UW) and useful Data (Data); inserting a Cyclic Prefix (CP) at a front end of the pilot signal; wherein N isuwNumber of training sequences, NCPThe number of points of the cyclic prefix;
LS channel estimation: estimating a time domain channel response of the pilot signal; the method comprises the following specific steps:
(1) for the read time domain pilot data UWsigDot by NuwPerforming point Fourier transform to obtain a frequency domain signal Y of the pilot signal;
Y＝fft(UWsig，Nuw)
(2) performing least square channel estimation on the frequency domain signal of the pilot signal and a pre-stored frequency domain signal X of a local pilot signal to obtain a frequency domain channel H of the pilot signal,
H＝Y/X
(3) converting the frequency domain channel of the pilot signal to a time domain to obtain a time domain channel h of the pilot signal;
h＝ifft(H，Nuw)
searching a maximum energy window: carrying out maximum energy window sliding search on the time domain impact response of the pilot channel, and circularly moving the time domain impact response to the left to move the starting point of the maximum energy window to the position of the starting point of the channel; the method comprises the following specific steps:
(1) as shown in fig. 3, the data of the N-1 point at the head of the time domain channel is spliced to the tail to form Nuw+ N-1 point channel estimation value; wherein,k is the search window length;
(2) sliding search maximum energy window: starting to search from the first point of the time domain channel impulse response, and calculating the energy sum P of k points each timekSequential sliding calculation of NuwThe sum of the energies;
finding NuwThe energy and the maximum value, and the starting point i of the maximum energy window;
[Pmax，i]＝max(Pk)
and (3) noise reduction treatment: the LS channel estimation is performed in the frequency domain, that is, the frequency domain channel of useful data can be obtained by interpolation after the frequency domain channel of the pilot is obtained, but the LS channel estimation does not consider the influence of noise, so the accuracy of the obtained channel is low, and it is necessary to perform noise reduction processing on the channel, and the noise reduction processing can be performed only in the time domain.
The specific noise reduction steps are as follows:
(1) calculating the average energy of the time domain impulse response of the pilot channel at each point outside the energy window as the noise power;
(2) setting the time domain impulse response of the pilot channel to be zero at each point outside the energy window;
(3) screening each point of the time domain impulse response of the pilot channel within the energy window according to the ratio of the maximum energy value to the noise power, and setting each path which does not pass through the threshold to be zero;
zero-filling of time domain channels: zero filling is carried out in the middle of the obtained time domain channel, and the channel length of useful data is filled to obtain the estimated time domain channel of the useful data; and then FFT is carried out on the time domain channel of the useful data to obtain the frequency domain channel of the useful data.
Claims (6)
1. A channel estimation and noise filtering method of a single carrier frequency domain equalization system is characterized in that: the method comprises the following steps:
step 1.1, a receiving end of a single carrier frequency domain equalization system reads M-point pilot signals and obtains a time domain channel by using an LS algorithm;
step 1.2, splicing the front N-1 point data of the time domain channel to the tail part thereof to form a new N + M-1 point time domain channel;
step 1.3, carrying out maximum energy window sliding search on the spliced time domain channel, and finding out the position with the maximum signal energy in the window;
step 1.4, noise estimation is carried out according to the data outside the window of the maximum energy window;
step 1.5, carrying out noise filtering processing on the time domain channel, namely carrying out noise filtering on the inner window energy diameter by taking noise as a threshold, and clearing the outer window energy diameter;
and step 1.6, obtaining a frequency domain channel of the useful signal according to the time domain channel after noise filtering.
2. The channel estimation and noise filtering method for single carrier frequency domain equalization system according to claim 1, wherein: in step 1.1, the LS algorithm is:
wherein Y is frequency domain data of the received pilot signal, X is frequency domain data of the local pilot signal, and the time domain channel estimation is
3. The channel estimation and noise filtering method for single carrier frequency domain equalization system according to claim 1, wherein: in step 1.3, the maximum energy window sliding search method specifically comprises the following steps:
1.3.1, the window length of the energy window is N, and N is greater than the multipath time delay of a channel;
1.3.2 said energy window sliding search from the kth data h of the new N + M-1 point time domain channelkStarting to calculate, sliding to obtain the energy sum P of continuous N datak：
1.3.3, screening out the maximum energy window and recording the initial position k.
4. The channel estimation and noise filtering method for single carrier frequency domain equalization system according to claim 1, wherein: in step 1.4, the noise estimation method specifically includes:
5. the channel estimation and noise filtering method for single carrier frequency domain equalization system according to claim 1, wherein: in step 1.5, the performing noise reduction processing on the time domain channel includes:
1.5.1, setting zero for each path of the time domain channel outside the maximum energy window;
1.5.2, screening each path of the time domain channel in the maximum energy window by taking the noise power as a threshold, and setting the point in the window which does not pass the noise threshold to be zero.
6. The channel estimation and noise filtering method for single carrier frequency domain equalization system according to claim 1, wherein: in step 1.6, the estimating of the frequency domain channel of the useful signal includes the steps of:
1.6.1, zero-filling the time domain channel of the M point pilot signal to the length of the useful signal to obtain the estimated time domain channel of the useful signal;
1.6.2, carrying out Fourier transform on the time domain channel of the useful signal to obtain a frequency domain channel of the useful signal.
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| US20110007792A1 (en) * | 2007-02-07 | 2011-01-13 | Masayuki Kimata | Apparatus for channel estimation, apparatus for equalization and method for equalization |
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Application publication date: 20200612 |