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WO2012122744A1 - Procédé d'extraction de paramètres d'un canal multidimensionnel - Google Patents

Procédé d'extraction de paramètres d'un canal multidimensionnel Download PDF

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Publication number
WO2012122744A1
WO2012122744A1 PCT/CN2011/075055 CN2011075055W WO2012122744A1 WO 2012122744 A1 WO2012122744 A1 WO 2012122744A1 CN 2011075055 W CN2011075055 W CN 2011075055W WO 2012122744 A1 WO2012122744 A1 WO 2012122744A1
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channel
measurement
channel parameter
snapshot
local area
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PCT/CN2011/075055
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English (en)
Chinese (zh)
Inventor
张建华
黄程祥
张平
刘宝玲
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北京邮电大学
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Publication of WO2012122744A1 publication Critical patent/WO2012122744A1/fr

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W28/00—Network traffic management; Network resource management
    • H04W28/16—Central resource management; Negotiation of resources or communication parameters, e.g. negotiating bandwidth or QoS [Quality of Service]
    • H04W28/18—Negotiating wireless communication parameters
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • 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
    • H04L25/0202—Channel estimation
    • H04L25/0204—Channel estimation of multiple channels
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • 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
    • H04L25/0202—Channel estimation
    • H04L25/0212—Channel estimation of impulse response
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • 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
    • H04L25/0202—Channel estimation
    • H04L25/0222—Estimation of channel variability, e.g. coherence bandwidth, coherence time, fading frequency
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • 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
    • H04L25/0202—Channel estimation
    • H04L25/024—Channel estimation channel estimation algorithms
    • H04L25/0242—Channel estimation channel estimation algorithms using matrix methods
    • H04L25/0244—Channel estimation channel estimation algorithms using matrix methods with inversion
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/10—Scheduling measurement reports ; Arrangements for measurement reports
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W28/00—Network traffic management; Network resource management
    • H04W28/02—Traffic management, e.g. flow control or congestion control
    • H04W28/04—Error control
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W64/00—Locating users or terminals or network equipment for network management purposes, e.g. mobility management

Definitions

  • the present invention relates to wireless communication technologies, and in particular, to a multi-dimensional channel parameter extraction method.
  • Multi-Input Multi-Output MIMO
  • MIMO Multiple input multiple output
  • This technology utilizes signals transmitted and received over multiple antennas to suppress channel fading, and can double the capacity and spectrum utilization of wireless communication systems without increasing bandwidth.
  • the performance of MIMO technology is also subject to the space-time fading characteristics of the channel, and the wideband channel will exhibit new frequency selection characteristics. Therefore, a suitable wideband MIMO channel model is established to study broadband MIMO.
  • the spatial, temporal and frequency three-dimensional fading characteristics of the channel are the premise and key to maximize the advantages of MIMO technology.
  • the MIMO channel model provides a reference for transmission technology, resource management and network planning in wireless communication systems.
  • channel parameter extraction is a key link in the channel modeling process.
  • a high-precision, multi-dimensional joint extraction method is needed.
  • the application is more widely used is the spatially alternating generalized expectation maximization method.
  • the method decomposes a multi-dimensional estimation problem into multiple one-dimensional estimation problems, and can jointly estimate various parameters of the multipath signal, and is not limited to the structure of the transmitting and receiving antenna array. .
  • Figure 1 is a schematic flow chart of an existing channel parameter estimation method. Referring to Figure 1, the process includes:
  • Step 101 Set a measurement snapshot sequence number k , and start channel parameter extraction on the kth measurement snapshot.
  • Step 102 Initialize channel parameters of all L- path signals by using a serial interference cancellation method to obtain initial values of channel parameters of all L- path signals.
  • step 103 the initial value of the iteration round n is set to 1, and the first round of iteration is started.
  • Step 104 Initialize the sequence number l of the multipath signal to 1, and start extracting the channel parameters of the first path signal.
  • Step 105 calculates a first signal path l conditional expectation.
  • Step 106 the search path of the first signal l maximizing the likelihood function of channel parameter value, to give the l-path channel parameter signal after the n-th iteration extraction result.
  • the search order so that the likelihood function maximizes propagation delay of the l-path signals, Doppler shift, away from the horizontal angle, vertical angle away from the horizontal angle of arrival, angle of arrival and polarization multiplexing vertical amplitude coefficients
  • other parameters remain fixed and equal to the value after the last update.
  • Step 107 Determine whether the sequence number l of the multipath signal is equal to the maximum multipath number L. If yes, the nth round of iteration ends, and the channel parameter extraction result of all L- path signals after the n-th iteration is obtained; otherwise, the sequence number l is incremented by 1, and the process returns to step 105.
  • Step 108 after the n-th wheel is determined iterative channel parameter extracting all L multipath signals whether the result of the result of the same n -1 iterations. If yes, the result is converged. The result is the final channel parameter extraction result of all the L- path signals of the kth measurement snapshot; otherwise, the result is not converged, n is incremented by 1, and the process returns to step 104.
  • Step 109 Determine whether the sequence number k of the measurement snapshot is equal to the maximum number of snapshots K. If so, the entire channel parameter extraction process ends; otherwise, k is incremented by 1, and the process returns to step 101.
  • the correlation between measurement snapshots is ignored, and the channel parameters of adjacent measurement snapshots are similar.
  • the channel parameter values are initialized independently using a serial interference cancellation method.
  • the serial interference cancellation method is less efficient and takes a long time in the actual execution process, so that the initialization process accounts for the execution time of the entire channel parameter extraction process. 70% or so.
  • the technical problem to be solved by the present invention is how to provide a multi-dimensional channel parameter extraction scheme to improve the efficiency of channel parameter initialization in the channel parameter extraction process, and at the same time improve the efficiency of searching channel parameter values that maximize the likelihood function.
  • the present invention provides a multi-dimensional channel parameter extraction method, the method comprising the steps of:
  • step S2 determining, according to the calculation result of step S1, a position of the current measurement snapshot within a range of the local area in which it is located;
  • step S3 The determination result is selected by using a serial interference cancellation method or a method for measuring correlation between snapshots to initialize channel parameters of the current measurement snapshot;
  • the priority search algorithm is used to iteratively calculate the channel parameters of each path, and the channel parameters are updated in the iterative operation according to the principle that the likelihood function of each path channel parameter is maximized and monotonously reduced.
  • the measurement device includes a mobile station, and the parameter setting of the measurement device and related information of the measurement environment include: a center carrier frequency f c of the measurement signal, a channel sampling rate f s , and a mobile station motion speed v .
  • the method for calculating the number of measurement snapshots included in the range d of each local area is: The symbol ⁇ ⁇ ⁇ indicates rounding down.
  • the method for determining the position of the current measurement snapshot in the range of the local area in the step S2 is: calculating ( kK 0 ) mod Q, where k is the sequence number of the current measurement snapshot, and K 0 is the initial value of the sequence number of the measurement snapshot. If the result of the above calculation is 0, the current measurement snapshot is the first measurement snapshot in the range of the local area in which it is located; if not, the current measurement snapshot is not the first in the range of the local area in which it is located. Measurement snapshots.
  • the serial interference cancellation method is used to initialize the path parameters of each path; otherwise, an initialization method based on measuring the correlation between snapshots is adopted.
  • ⁇ l (0) ( k ) indicates the initial value of the channel parameter of the l- th path signal in the kth measurement snapshot
  • ⁇ l ( R ) ( k -1) represents the final channel parameter extraction result of the l -th path signal in the k -th measurement snapshot
  • L is The maximum number of multipaths.
  • the prioritized search strategy is: Wherein [theta] l (n) represents a channel parameter value of l-path signal after the n-th iteration, the U-l for the first search field, z ( ⁇ l) is the likelihood function of l-path signal, the first search field is defined as The union of the intervals with a certain multiple of the search step radius, centered on the corresponding channel parameter values of the other L -1 path signals.
  • the priority search field is calculated as follows: Where ⁇ represents the search step size and ⁇ is a positive integer representing the weight of the search step size.
  • updating the channel parameter according to the principle that the likelihood function of each channel parameter is monotonous or not decreases means: whether the judgment formula z ( ⁇ l ( n ) ) ⁇ z ( ⁇ l ( n -1) ) is established, and if so, channel parameters will be the l-path signal updates the value of [theta] l (n), otherwise continue supplemented focus the search channel parameter priority search area, where [theta] l (n) represents the channel parameters of l-path signal after the n-th iteration The value, z ( ⁇ l ) is the likelihood function of the l- th path signal.
  • the invention utilizes a method for measuring the path parameters of the measurement snapshot based on the method for measuring the correlation between snapshots, so that for most measurement snapshots, the calculation process of the initial values of the channel parameters in the channel parameter extraction process is actually omitted, therefore,
  • the efficiency of channel parameter initialization in the channel parameter extraction process is improved; the iterative operation is performed on each channel parameter by using a prioritized search strategy, which improves the efficiency of searching for channel parameter values that maximize the likelihood function.
  • FIG. 1 is a schematic flowchart of an existing channel parameter extraction method
  • FIG. 3 is a flowchart of a multi-dimensional channel parameter extraction method according to an embodiment of the present invention.
  • FIG. 4 is a specific flowchart of performing multi-dimensional channel parameter extraction according to an embodiment of the present invention.
  • image 3 A flowchart of a multi-dimensional channel parameter extraction method according to an embodiment of the present invention. Referring to FIG. 3 and referring to steps S1 to S4 of FIG. 2, the process of the method includes:
  • Step 201 setting a sequence number k of the measurement snapshot
  • Step 202 Initialize channel parameters of the L- path signal by using a serial interference cancellation method or an initialization method based on measuring correlation between snapshots, and obtain initial values of channel parameters of all L- path signals, where L is a positive integer.
  • the concept of a local area is defined: dividing a continuous measurement route into multiple local areas. For the first measurement snapshots of each local area, the interference cancellation method used to initialize all the parameters of the L channel signal path; snapshots for other measurements, initialization method for initializing the correlation between measured based on the snapshot, i.e. The initial channel parameter extraction result of the previous measurement snapshot is directly used as the initial value of the channel parameter of all the L- path signals in the measurement snapshot. Thus, for most measurement snapshots, the calculation process of the initial values of the channel parameters in the channel parameter extraction process is actually omitted, and the efficiency of channel parameter initialization is improved.
  • step 203 the initial value of the iteration round n is set to 1, and the first round of iteration is prepared.
  • Step 204 Initialize the sequence number l of the multipath signal to 1, and prepare to start extracting the channel parameters of the first path signal.
  • Step 205 calculates a first signal path l conditional expectation.
  • Step 206 a search using a search strategy with priority so maximizing the likelihood function of the channel parameters of the multipath signals l, l to obtain the channel parameters of the multipath signals in the n-th iteration extraction result.
  • the search order of the first signal path l maximizing the likelihood function of propagation delay, Doppler shift, away from the horizontal angle, vertical angle away from the horizontal angle of arrival, angle of arrival and polarization multiplexing vertical amplitude coefficients
  • Such parameters when searching for a certain parameter, keep the other parameters fixed and fixed to the last updated value.
  • a priority search field is defined for the parameter, and the priority search field is defined as a certain multiple of the search step (preset value) with the corresponding parameter value of the other L -1 path signal as the center.
  • the search is first performed in the priority search domain to find out whether there is a parameter value that maximizes the likelihood function and monotonically decreases, and if so, updates the corresponding parameter to the parameter value; otherwise, the search in the non-first search domain is satisfied.
  • the parameter value of the above condition (maximizing the likelihood function and monotonously decreasing).
  • Step 207 Determine whether the sequence number l of the multipath signal is equal to the maximum multipath number L. If yes, the nth round of iteration ends, and the channel parameter extraction result of all L- path signals after the n-th iteration is obtained; otherwise, l is incremented by 1, and the process returns to step 205.
  • Step 208 after the n-th wheel is determined iterative channel parameter extracting all L multipath signals whether the result of the result of the same n -1 iterations. If yes, the result is converged. The result is the final channel parameter extraction result of all the L- path signals of the kth measurement snapshot; otherwise, the result does not converge, n is incremented by 1, and the process returns to step 204.
  • Step 209 Determine whether the sequence number k of the measurement snapshot is equal to the preset maximum number of snapshots K. If so, the entire channel parameter extraction process ends; otherwise, k is incremented by 1, and the process returns to step 201.
  • FIG. 4 is a specific flowchart of performing multi-dimensional channel parameter extraction according to an embodiment of the present invention. Referring to Figure 4, the process includes:
  • Step 301 Calculate a range of the local area and a number of measurement snapshots included in each local area according to the parameter setting of the measurement device and the related information of the measurement environment during the channel measurement process (this step is a preparation step performed before step 201).
  • the measuring device is a tool for measuring channel parameters, and mainly includes a transmitting unit for transmitting data, a receiving unit (that is, a mobile station) for receiving data, a data storage unit for storing data, and a transmitting and receiving antenna.
  • the center carrier frequency of the transmitted and received signals during measurement is f c
  • Step 302 Set a sequence number k of the measurement snapshot. (This step corresponds to step 201)
  • Step 303 Determine, according to the calculation result, a position of the current measurement snapshot in the local area where the measurement snapshot is located, that is, determine whether the kth measurement snapshot is the first measurement snapshot in the local area in which it is located. If yes, go to step 304; if no, go to step 305.
  • the judgment method is as follows: the starting sequence number of the measurement snapshot is K 0 , K 0 > 0 and is an integer, and the calculation is: ( k - K 0 ) mod Q where mod represents the remainder. If the result of the above calculation is 0, the kth measurement snapshot is the first measurement snapshot in the local area in which it is located. If not equal to 0, the kth measurement snapshot is not the first in the local area in which it is located. Measure the snapshot.
  • Step 304 If the kth measurement snapshot is the first measurement snapshot in the local area in which it is located, the channel interference parameter is used to initialize the channel parameters of all the L path signals included in the local area to obtain all the L path signals. The initial value of the channel parameter.
  • the serial interference cancellation initialization method is used for the first measurement snapshot in each local area, which can avoid or mitigate the error accumulation caused by the initialization method based on measuring the correlation between snapshots.
  • Step 305 If the kth measurement snapshot is not the first measurement snapshot in the local area, the result of the final channel parameter extraction result of the k -1th measurement snapshot is directly used as the L path in the kth measurement snapshot. The initial value of the channel parameter of the signal.
  • step 306 the initial value of the iteration round n is set to 1, and the first round of iteration is started. This step corresponds to step 203.
  • Step 307 Initialize the sequence number l of the multipath signal to 1, and prepare to start extracting the channel parameters of the first path signal. This step corresponds to step 204.
  • Step 308 calculating the first l The condition of the path signal is expected. This step corresponds to step 205.
  • Step 309 determining the first l The preferred search field for each channel parameter in the path signal.
  • the first l Priority search field for each channel parameter in the path signal U l Defined as other L -1
  • the corresponding channel parameter value of the path signal is the center, and the union of the intervals with a certain multiple of the search step radius is
  • ⁇ l ( n ) ( k ) ⁇ A l ( n ) , ⁇ l ( n ) , ⁇ 1, l ( n ) , ⁇ 1, l ( n ) , ⁇ 2, l ( n ) , ⁇ 2, l ( n ) , f d,l ( n )
  • ⁇ indicates the first n
  • ⁇ represents the search step size
  • ⁇ is a positive integer representing the weighting of the search step
  • ' U ' to the right of the equal sign indicates the union.
  • ⁇ l ( n ) ( k ) abbreviated as ⁇ l ( n ) .
  • the priority search fields of propagation delay, Doppler shift, horizontal exit angle, vertical exit angle, horizontal arrival angle, and vertical arrival angle are respectively among them, Search steps for propagation delay, horizontal exit angle, vertical exit angle, horizontal arrival angle, vertical angle of arrival, and Doppler shift, respectively
  • the weighting coefficients of the respective step lengths are respectively indicated, and the coefficients are flexibly adjusted according to the proportion of the search step size in the entire value range. E.g ⁇ ⁇ Generally take 1 , when the search step of the angle domain is 2 °, Generally take 2 .
  • Step 310 to find the first signal path l maximizes the likelihood function of propagation delay values first search field.
  • Likelihood function of path signal l Expressed as among them Which symbol Represents the Kronecker product, ( ⁇ ) H represents the conjugate transpose of the matrix, Where the symbol ( . ) * denotes a conjugate, X l ( ⁇ l , f d, l ) is a matrix of N ⁇ M dimensions, and N and M are the total number of receiving and transmitting antennas, respectively.
  • Step 311 Determine whether the likelihood function is monotonous or not.
  • the propagation delay value that was found in the previous step to maximize the likelihood function must satisfy the condition that the likelihood function monotonically decreases, and it is possible that it is the optimal value in the entire delay value range.
  • the condition that the likelihood function monotonically decreases in this step is expressed as z ( ⁇ 1, l ( n -1) , ⁇ 1, l ( n- 1) , ⁇ 2, l ( n- 1) , ⁇ 2, l ( n- 1) , ⁇ l ( n ) , f d,l ( n -1) ; x l ) ⁇ z ( ⁇ 1, l ( n -1) , ⁇ 1, l ( n- 1) , ⁇ 2, l ( n- 1) , ⁇ 2, l ( n- 1) , ⁇ l ( n- 1) , ⁇ l ( n- 1) , f d,l ( n -1) ;
  • Step 312 to find the first signal path l maximizes the likelihood function of the non-preferential propagation delay value search field.
  • the search process in this step is expressed as among them Express Complementary. Since the likelihood function is inevitably monotonous, if this step is performed, the ⁇ l ( n ) obtained in this step is necessarily the optimal in the entire delay value range.
  • Step 313 in the first search field to find the first signal path l maximizing the likelihood function of Doppler shift values.
  • the process of finding the Doppler shift value that maximizes the likelihood function in the priority search domain in this step can be expressed as
  • step 314 it is determined whether the likelihood function is monotonous or not.
  • the Doppler shift value that was found in the previous step to maximize the likelihood function must satisfy the condition that the likelihood function monotonically does not decrease, and it is possible that it is the optimal value in the entire Doppler shift range.
  • step 313 The condition that the likelihood function monotonically decreases in this step is expressed as z ( ⁇ 1, l ( n -1) , ⁇ 1, l ( n- 1) , ⁇ 2, l ( n- 1) , ⁇ 2, l ( n- 1) , ⁇ l ( n ) , f d,l ( n ) ; x l ) ⁇ z ( ⁇ 1, l ( n -1) , ⁇ 1, l ( n- 1) , ⁇ 2, l ( n- 1) , ⁇ 2, l ( n- 1) , ⁇ 2, l ( n- 1) , ⁇ l ( n ) , f d,l ( n -1) ; x l ) If the condition shown in the above formula is satisfied, step 313 The obtained f d,l ( n ) is the Doppler shift value of the l- th path signal after the n-th iteration, skipping step
  • Step 315 the non-first search domain to find the first signal path l maximizing the likelihood function of Doppler frequency shift values.
  • the search process in this step is expressed as among them Express Complementary. Since the likelihood function is inevitably monotonous, if this step is performed, the f d,l ( n ) obtained in this step is necessarily the optimal in the entire Doppler shift value range.
  • Step 316 in the first search field to find the first l-path signal level maximizes the likelihood function value departure angle.
  • the process of finding the horizontal leaving angle value that maximizes the likelihood function in the priority search domain in this step can be expressed as
  • Step 317 Determine whether the likelihood function is monotonous or not.
  • the horizontal leaving angle value that is found in the previous step to maximize the likelihood function must satisfy the condition that the likelihood function monotonically does not decrease, and it is possible that the horizontal value of the entire horizontal leaving angle is the optimal value.
  • step 316 is obtained.
  • step 318 As the first n After the iteration l The horizontal value of the path signal leaves the angle value. Skip step 318 and directly perform step 319. If not, then step 316 ⁇ 1 ,l ( n ) It is not possible to optimize the entire horizontal departure angle range, and step 318 is performed.
  • Step 318 looking for the first in the non-first search domain l
  • the likelihood function of the path signal maximizes the horizontal departure angle value.
  • the search process in this step is expressed as among them Express Complementary. Since the likelihood function is inevitably monotonous, if this step is performed, the step is obtained. ⁇ 1 ,l ( n ) It must be the best in the entire horizontal departure angle range.
  • Step 319 the first search field to find the first signal path l maximizing the likelihood function value of the angle away from vertical.
  • the process of finding the vertical departure angle value that maximizes the likelihood function in the priority search domain in this step can be expressed as
  • step 320 it is determined whether the likelihood function is monotonous or not.
  • the value of the vertical departure angle obtained by the previous step to maximize the likelihood function must satisfy the condition that the likelihood function monotonically does not decrease, and it is possible that it is the optimal value in the entire vertical departure angle range.
  • step 319 If the condition shown in the above formula is satisfied, then step 319 is obtained.
  • ⁇ 1 , l ( n ) is the vertical departure angle value of the l- th path signal after the n-th iteration, skipping step 321 and directly performing step 322; if not, step 319 obtains ⁇ 1 , l ( n ) It is impossible to optimize the entire vertical departure angle range, and step 321 is performed.
  • Step 321 the non-first search domain to find the first signal path l maximizes the likelihood function of the angle away from vertical value.
  • the search process in this step is expressed as among them Express Complementary. Since the likelihood function is inevitably monotonous, if this step is performed, the ⁇ 1, l ( n ) obtained in this step is necessarily the best in the entire vertical departure angle range.
  • Step 322 in the first search field to find the first l-path signal level maximizes the likelihood function value of the angle of arrival.
  • the process of finding the horizontal arrival angle value that maximizes the likelihood function in the priority search domain in this step can be expressed as
  • Step 323 Determine whether the likelihood function is monotonous or not.
  • the horizontal arrival angle value found in the previous step to maximize the likelihood function must satisfy the condition that the likelihood function monotonically does not decrease, and it is possible that it is the optimal value in the entire horizontal arrival angle range.
  • the condition that the likelihood function monotonously decreases in this step is expressed as z ( ⁇ 1, l ( n ) , ⁇ 1, l ( n ) , ⁇ 2, l ( n ) , ⁇ 2, l ( n- 1) , ⁇ l ( n ) , f d,l ( n ) ; x l ) ⁇ z ( ⁇ 1, l ( n ) , ⁇ 1, l ( n ) , ⁇ 2, l ( n- 1) , ⁇ 2, l ( n- 1) , ⁇ l ( n ) , f d,l ( n ) ; x l If the condition shown in the above formula is satisfied,
  • step 324 and directly perform step 325. If not, then step 322 ⁇ 2, l ( n ) It is not possible to optimize the entire horizontal arrival angle range, and step 324 is performed.
  • Step 324 looking for the first in the non-first search domain l
  • the horizontal signal of the diameter signal maximizes the angle of arrival.
  • the search process in this step is expressed as among them Express Complementary. Since the likelihood function is inevitably monotonous, if this step is performed, the step is obtained. ⁇ 2, l ( n ) It must be the optimal in the entire horizontal angle of arrival.
  • Step 325 in the first search field to find the first signal path l maximizing the likelihood function of the vertical angle of arrival values.
  • the process of finding the vertical angle of arrival value that maximizes the likelihood function in the priority search domain in this step can be expressed as
  • Step 326 Determine whether the likelihood function is monotonous or not.
  • the vertical angle of arrival value found in the previous step to maximize the likelihood function must satisfy the condition that the likelihood function monotonically does not decrease, and it is possible that it is the optimal value in the entire vertical angle of arrival.
  • the condition that the likelihood function monotonously decreases in this step is expressed as z ( ⁇ 1, l ( n ) , ⁇ 1, l ( n ) , ⁇ 2, l ( n ) , ⁇ 2, l ( n ) , ⁇ l ( n ) , f d,l ( n ) ; x l ) ⁇ z ( ⁇ 1, l ( n ) , ⁇ 1, l ( n ) , ⁇ 2, l ( n ) , ⁇ 2, l ( n- 1) , ⁇ l ( n ) , f d,l ( n ) ; x l If the condition shown in the above formula is satisfied
  • step 327 As the first n After the iteration l The vertical arrival angle value of the path signal is skipped to step 327, and step 328 is directly executed. If not, then step 325 ⁇ 2 ,l ( n ) It is impossible to be optimal in the entire vertical angle of arrival range, and step 327 is performed.
  • Step 327 the non-first search domain to find the first signal path l maximizing the likelihood function of the vertical angle of arrival values.
  • the search process in this step is expressed as among them Express Complementary. Since the likelihood function is inevitably monotonous, if this step is performed, the ⁇ 2, l ( n ) obtained in this step is necessarily the optimal in the entire vertical angle of arrival.
  • Step 328 calculates a first polarization multiplexing l-path signal amplitude coefficients.
  • the polarization complex amplitude coefficient is calculated as Where the symbol ( ⁇ ) -1 represents the matrix inversion.
  • This step directly calculates the polarization complex amplitude coefficient, so there is no need to calculate its priority search field in step 308.
  • the above steps 309 ⁇ 328 correspond to step 206.
  • Step 329 Determine whether the sequence number l of the multipath signal is equal to the maximum multipath number L. If yes, the nth round of iteration ends, and the channel parameter extraction result of all the L- path signals after the n-th iteration is obtained; otherwise, l is incremented by 1, and the process returns to step 308. This step corresponds to step 207.
  • Step 331 Determine whether the sequence number k of the measurement snapshot is equal to the maximum number of snapshots K. If so, the entire channel parameter extraction process ends; otherwise, k is incremented by 1, and the process returns to step 302. This step corresponds to step 209.
  • the above embodiments are merely illustrative of the present invention and are not intended to be limiting of the invention, and various modifications and changes can be made without departing from the spirit and scope of the invention. Equivalent technical solutions are also within the scope of the invention, and the scope of the invention is defined by the claims.

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  • Mobile Radio Communication Systems (AREA)

Abstract

La présente invention concerne un procédé d'extraction de paramètres d'un canal multidimensionnel, et le procédé comprend les étapes suivantes : S1, calculer des plages de zones locales et le nombre d'instantanés de mesure contenus dans la plage de chaque zone locale conformément à des définitions de paramètre d'un dispositif de mesure et d'informations se rapportant à l'environnement de mesure dans le procédé de mesure de canal ; S2, déterminer la position d'un instantané de mesure actuel dans la plage de la zone locale où il est situé conformément aux résultats calculés en S1 ; S3, amorcer chaque paramètre de canal de chemin de l'instantané de mesure actuel en sélectionnant un procédé d'élimination d'interférence en série ou à l'aide d'un procédé basé sur les corrélations des instantanés de mesure conformément aux résultats déterminés en S2 ; S4, exécuter une opération d'itération sur chaque paramètre de canal de chemin en faisant appel à une stratégie de recherche avec priorité, et mettre à jour les paramètres de canal conformément aux principes selon lesquels la fonction de probabilité de chaque paramètre de canal de chemin est maximisée et monotone non décroissante dans le procédé d'itération. Avec l'application de la présente invention, l'efficacité d'un procédé d'extraction de paramètre de canal multidimensionnel est améliorée, tout en assurant la précision du résultat extrait.
PCT/CN2011/075055 2011-03-15 2011-05-31 Procédé d'extraction de paramètres d'un canal multidimensionnel WO2012122744A1 (fr)

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