CN114006797A - Multi-antenna equalization receiving method for high-speed video communication - Google Patents

Multi-antenna equalization receiving method for high-speed video communication Download PDF

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CN114006797A
CN114006797A CN202111637448.0A CN202111637448A CN114006797A CN 114006797 A CN114006797 A CN 114006797A CN 202111637448 A CN202111637448 A CN 202111637448A CN 114006797 A CN114006797 A CN 114006797A
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equalizer
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matrix
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antenna
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王少华
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Yuanzhi Technology Group Co ltd
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    • 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
    • H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
    • H04L25/03006—Arrangements for removing intersymbol interference
    • H04L25/03178—Arrangements involving sequence estimation techniques
    • H04L25/03248—Arrangements for operating in conjunction with other apparatus
    • H04L25/03254—Operation with other circuitry for removing intersymbol interference
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/30—Monitoring; Testing of propagation channels
    • H04B17/391—Modelling the propagation channel
    • H04B17/3912—Simulation models, e.g. distribution of spectral power density or received signal strength indicator [RSSI] for a given geographic region
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • 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
    • H04B7/0413—MIMO systems
    • 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
    • H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
    • H04L25/03891—Spatial equalizers
    • 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
    • H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
    • H04L25/03891—Spatial equalizers
    • H04L25/03961—Spatial equalizers design criteria
    • H04L25/03968—Spatial equalizers design criteria mean-square error [MSE]

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Abstract

The invention discloses a multi-antenna equalization receiving method for high-speed video communication, which comprises the following steps: defining variables
Figure DEST_PATH_IMAGE002
Constructing an adaptive filter; vector the column
Figure DEST_PATH_IMAGE004
As an input to the transversal filter, a filter is provided,
Figure DEST_PATH_IMAGE006
as a transverse filter tap coefficient, simplifying the nonlinear structure of the equalizer into a linear filtering structure; obtaining the optimal solution of the equalizer according to the least mean square error rule
Figure DEST_PATH_IMAGE008
(ii) a Through iterative solution of conjugate gradient algorithm
Figure 126986DEST_PATH_IMAGE008
And completing the design of the self-adaptive equalizer to ensure that the equalized overall channel is an identity matrix or a switching matrix. The invention models the adaptive equalization problem into the adaptive filtering problem, and solves the problem through CG algorithm iteration, and the equalizer adopting MMSE equalization does not need to identify the channel and can adapt to the change of the channel.

Description

Multi-antenna equalization receiving method for high-speed video communication
Technical Field
The invention relates to the technical field of communication signal processing, in particular to a multi-antenna equalization receiving method for high-speed video communication.
Background
With the development of modern communication technology and services, people have changed from the original single voice demand to the video and audio communication demand, so that the video communication service integrating voice, data and video transmission becomes a hotspot for the development of the communication field, and with the increasing dependence on the video communication service, the requirement on the quality of service is higher.
The video protocol in the current video communication is mainly based on the SIP and h.323 protocol, and h.323 specifies the operation mode required by the cooperative work of different audio, video and data terminals, which is the dominant standard in the technical fields of internet phone, teleconference and video conference.
The voice codec mainly takes g.711 and g.729 protocols as main protocols and provides voice access of traditional audio equipment, the video codec mainly takes h.264 and h.265 algorithms as main algorithms, and the difference between h.265 and h.264 means that the former can use less bandwidth to provide the same function, and the cost is the equipment computing power: h.265 encoded video requires more computing power to decode. The monitoring protocol mainly takes GB/T28181, ONIVF and RTSP as main components to realize the scheduling of audio and video data.
Information theory has proved that when different receiving antennas and different transmitting antennas are not related to each other, a Multiple Input and Multiple Output (Multiple Input and Multiple Output) system can well improve the anti-fading and noise performance of the system, thereby obtaining huge capacity, therefore, at a base station and a receiving end, by increasing the number of transmitting and receiving antennas, and adopting Multiple antennas to transmit and receive data, spectrum resources can be fully developed and utilized, and the communication efficiency is greatly improved. However, frequency selective fading due to multipath effect and time selective fading due to doppler shift cause problems such as channel interference and intersymbol interference.
Therefore, in order to reduce the transmission interference of the wireless channel and make better use of the MIMO technology, it is necessary to study the channel characteristics, particularly the spatial characteristics, and to improve the reliability of data transmission by using a signal processing technique of channel equalization at the receiving end. Considering that wireless channels tend to be time-varying, the equalizer is also set to be adaptive.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a multi-antenna equalization receiving method for high-speed video communication, which can reduce the problems of intersymbol interference, interchannel interference and the like caused by frequency selective fading and time selective fading of a wireless channel.
In order to achieve the purpose, the invention adopts the following technical scheme:
a multi-antenna equalization receiving method for high-speed video communication is provided, wherein a base station is provided with M antennas, a terminal is provided with N antennas, and the transmitting signals of the base station antennas are represented as follows:
Figure 229208DEST_PATH_IMAGE001
the terminal receives the signal as:
Figure 308023DEST_PATH_IMAGE002
the wideband MIMO wireless channel is represented as
Figure 806000DEST_PATH_IMAGE003
，
Figure 249751DEST_PATH_IMAGE004
Representing a transpose; receiving a signal
Figure 465969DEST_PATH_IMAGE005
And transmit the signal
Figure 348474DEST_PATH_IMAGE006
The relationship between them is:
Figure 389373DEST_PATH_IMAGE007
the received signal after adding the equalizer is expressed as:
Figure 331922DEST_PATH_IMAGE008
(ii) a G denotes the equalized overall channel, i.e.
Figure 769856DEST_PATH_IMAGE009
，
Figure 128156DEST_PATH_IMAGE010
It is shown that the equalizer,
Figure 600726DEST_PATH_IMAGE011
representing time delay and representing convolution operation;
the multi-antenna equalization receiving method comprises the following steps:
s1, obtaining the equalized second signal of the equalizeriAn output
Figure 448596DEST_PATH_IMAGE012
：
Figure 560778DEST_PATH_IMAGE013
In the formula (I), the compound is shown in the specification,
Figure 785086DEST_PATH_IMAGE014
、
Figure 112162DEST_PATH_IMAGE015
respectively a feedforward coefficient and a feedback coefficient output by the equalizer;
Figure 334196DEST_PATH_IMAGE016
、
Figure 746723DEST_PATH_IMAGE017
respectively before equalization of the equalizerjAn input and aiThe output of the first and second processors is,
Figure 509142DEST_PATH_IMAGE018
，
Figure 376211DEST_PATH_IMAGE019
；
s2, defining variables:
Figure 831463DEST_PATH_IMAGE020
respectively representing a signal matrix and a coefficient matrix,
Figure 731286DEST_PATH_IMAGE021
and
Figure 297396DEST_PATH_IMAGE022
respectively represent
Figure 271168DEST_PATH_IMAGE023
And
Figure 897322DEST_PATH_IMAGE024
i.e., a feed-forward coefficient matrix and a feedback coefficient matrix,
Figure 284441DEST_PATH_IMAGE025
representing a coefficient matrix formed by the feedforward coefficient matrix and the feedback coefficient matrix; will be the first of the equalizeriAn output
Figure 575614DEST_PATH_IMAGE012
Is converted into
Figure 731789DEST_PATH_IMAGE026
(ii) a At the receiving endiThe error of each output is expressed as
Figure 528843DEST_PATH_IMAGE027
；
Figure 75362DEST_PATH_IMAGE028
Represents a conjugate transpose;
s3, constructing an adaptive filter and converting the column vector
Figure 248855DEST_PATH_IMAGE029
As an input to the transversal filter, a filter is provided,
Figure 259536DEST_PATH_IMAGE030
as the transversal filter tap coefficients,
Figure 915908DEST_PATH_IMAGE017
as the desired signal, the output of the transversal filter
Figure 12039DEST_PATH_IMAGE012
Simplifying the nonlinear structure of the equalizer into a linear filtering structure for the user information to be acquired;
s4, according to the minimum mean square error rule, the expected signal is transmitted
Figure 458064DEST_PATH_IMAGE017
By using
Figure 526514DEST_PATH_IMAGE031
Expressed, the optimal solution for the equalizer is expressed as:
Figure 665372DEST_PATH_IMAGE032
the optimal solution of the equalizer is expressed by Wiener-Holf equation as:
Figure 248800DEST_PATH_IMAGE033
wherein the content of the first and second substances,
Figure 685466DEST_PATH_IMAGE034
，
Figure 670740DEST_PATH_IMAGE035
represents a conjugate operation;
s5, solving the solution by a conjugate gradient algorithm
Figure 980498DEST_PATH_IMAGE036
And completing the design of the self-adaptive equalizer to ensure that the equalized overall channel is an identity matrix or a switching matrix.
In order to optimize the technical scheme, the specific measures adopted further comprise:
further, the wideband MIMO wireless channel is represented as:
Figure 51223DEST_PATH_IMAGE037
in the formula (I), the compound is shown in the specification,
Figure 42312DEST_PATH_IMAGE038
is the firstlThe delay of the strip path is such that,
Figure 882092DEST_PATH_IMAGE039
the function of the impact is expressed as,
Figure 362752DEST_PATH_IMAGE040
correspond to the firstlThe time delay of the strip path is,
Figure 364117DEST_PATH_IMAGE041
is as followslChannel transfer matrix for a strip path:
Figure 221214DEST_PATH_IMAGE042
in the formula (I), the compound is shown in the specification,
Figure 915501DEST_PATH_IMAGE043
is the first to represent the transmitting end
Figure 504745DEST_PATH_IMAGE044
Root antenna to receiving end
Figure 550062DEST_PATH_IMAGE045
Between the root antennaslThe channel gain of the strip path is,
Figure 945271DEST_PATH_IMAGE046
indicating the number of resolvable multipaths,
Figure 681014DEST_PATH_IMAGE047
，
Figure 769056DEST_PATH_IMAGE048
。
further, on the basis of the correlation of a given MIMO channel, the channel transmission coefficients are simulated by the following formula:
Figure 36089DEST_PATH_IMAGE049
in the formula (I), the compound is shown in the specification,
Figure 907094DEST_PATH_IMAGE050
；
Figure 575972DEST_PATH_IMAGE051
is defined in the power delay profilelPower of each resolvable path;
Figure 834915DEST_PATH_IMAGE052
is that
Figure 12081DEST_PATH_IMAGE053
By a transmit-side correlation matrix
Figure 14672DEST_PATH_IMAGE054
Correlation matrix with receiving end
Figure 538057DEST_PATH_IMAGE055
Obtained as a Kroneckor product, i.e.
Figure 702322DEST_PATH_IMAGE056
；
Figure 881631DEST_PATH_IMAGE057
Each of which
Figure 422334DEST_PATH_IMAGE058
Representing mutually independent small-scale fading in each path, vector a is generated by a simulation method of a single-antenna channel, because there are M x N different paths from the transmitting antenna to the receiving antenna,
Figure 800225DEST_PATH_IMAGE059
。
further, in step S5, the solution is iteratively solved by a conjugate gradient algorithm
Figure 587922DEST_PATH_IMAGE060
Comprises the following steps:
according to the structure of the equalizer, iteratively updating the filter coefficient by adopting an adjusted conjugate gradient algorithm until convergence; the adjusted conjugate gradient algorithm is as follows:
Figure 51264DEST_PATH_IMAGE061
Figure 395658DEST_PATH_IMAGE062
Figure 831318DEST_PATH_IMAGE063
Figure 337386DEST_PATH_IMAGE064
Figure 553604DEST_PATH_IMAGE065
；
wherein, the first and second guide rollers are arranged in a row,
Figure 121595DEST_PATH_IMAGE066
generally, 1 is taken to adjust the step size,
Figure 474079DEST_PATH_IMAGE067
is an input vector
Figure 151048DEST_PATH_IMAGE068
The correlation matrix of (a) is calculated,
Figure 526666DEST_PATH_IMAGE069
which represents a direction vector of the light beam,
Figure 212862DEST_PATH_IMAGE070
the step size is represented as a function of time,
Figure 419852DEST_PATH_IMAGE071
which represents the vector of the residual error,
Figure 533302DEST_PATH_IMAGE072
is orthogonal
Figure 645483DEST_PATH_IMAGE069
The vector of the vector is then calculated,
Figure 869791DEST_PATH_IMAGE073
representing the forgetting factor corresponding to the feedback coefficient of the jth receiving antenna,
Figure 196867DEST_PATH_IMAGE074
indicating the expected value of the output.
The cost function used is:
Figure 418901DEST_PATH_IMAGE075
；
wherein the content of the first and second substances,brepresenting an association vector between the input data and the expected value.
Calculated using exponentially decaying data windows
Figure 565849DEST_PATH_IMAGE067
And
Figure 593848DEST_PATH_IMAGE076
：
Figure 463846DEST_PATH_IMAGE077
Figure 919098DEST_PATH_IMAGE078
。
wherein the content of the first and second substances,
Figure 818921DEST_PATH_IMAGE079
is shown as
Figure 322714DEST_PATH_IMAGE080
And the forgetting factor corresponding to the individual expression.
The invention designs an efficient self-adaptive equalizer at a receiving end, and the efficient self-adaptive equalizer is defined
Figure 358803DEST_PATH_IMAGE029
And
Figure 984957DEST_PATH_IMAGE025
converting the ith output of the equalizer to
Figure 293447DEST_PATH_IMAGE081
(ii) a Constructing an adaptive filter by combining the column vectors
Figure 663249DEST_PATH_IMAGE029
As input to the transversal filter, column vectors
Figure 819424DEST_PATH_IMAGE030
The elements in (2) are regarded as transversal filter tap coefficients, so that a feedback decision maker (DFE) structure with a nonlinear structure is simplified into a linear structure, and an adaptive equalization problem is modeled into an adaptive filtering problem. Then, according to the MMSE rule, the MMSE solution of the equalizer is obtained
Figure 554161DEST_PATH_IMAGE036
After the expression is carried out by using a Wiener-Holf equation, the solution is iterated by a CG algorithm.
The invention has the beneficial effects that:
(1) the multi-antenna equalization receiving method for high-speed video communication does not need to identify the channel by the equalizer adopting MMSE equalization, and can adapt to the change of the channel.
(2) The multi-antenna equalization receiving method for high-speed video communication adopts CG algorithm to calculate and obtain MMSE solution of the equalizer, carries out compromise processing on convergence speed and operation complexity, and is suitable for a high-speed video communication system.
(3) The CG algorithm adopted by the invention does not need calculation
Figure 162997DEST_PATH_IMAGE082
Avoid when estimating
Figure 70910DEST_PATH_IMAGE082
When the positive definite characteristic is lost, the algorithm is not converged.
Drawings
Fig. 1 is a transmit receive antenna array model.
Fig. 2 is a diagram of a spatial channel simulation process.
Fig. 3 is a schematic diagram of an adaptive equalizer structure.
Fig. 4 is a schematic diagram of an adaptive filter structure.
Fig. 5 is a rule of error rate performance of three equalization techniques in a 2 × 2MIMO system as a function of signal-to-noise ratio.
Detailed Description
The present invention will now be described in further detail with reference to the accompanying drawings.
It should be noted that the terms "upper", "lower", "left", "right", "front", "back", etc. used in the present invention are for clarity of description only, and are not intended to limit the scope of the present invention, and the relative relationship between the terms and the terms is not limited by the technical contents of the essential changes.
The symbols represent: in this example
Figure 767078DEST_PATH_IMAGE084
，
Figure 735034DEST_PATH_IMAGE086
，
Figure 831166DEST_PATH_IMAGE088
And
Figure 542770DEST_PATH_IMAGE090
the method is characterized by comprising the steps of transposition, conjugate transposition, inversion and conjugate operation, wherein bold capital letters represent matrixes, bold lowercase letters represent vectors, and stars represent convolution operation.
The multi-antenna equalization receiving method of the embodiment comprises the following steps:
s1, obtaining the ith output of the equalizer
Figure 611220DEST_PATH_IMAGE091
：
Figure 750077DEST_PATH_IMAGE013
In the formula (I), the compound is shown in the specification,
Figure 67926DEST_PATH_IMAGE092
、
Figure 770172DEST_PATH_IMAGE093
respectively a feedforward coefficient and a feedback coefficient output by the equalizer;
Figure 755445DEST_PATH_IMAGE094
、
Figure 65204DEST_PATH_IMAGE095
respectively before equalization of the equalizerjAn input and aiThe output of the first and second processors is,
Figure 808032DEST_PATH_IMAGE096
，
Figure 861439DEST_PATH_IMAGE097
。
s2, defining variables:
Figure 701219DEST_PATH_IMAGE098
the ith output of the equalizer
Figure 870294DEST_PATH_IMAGE091
Is converted into
Figure 428314DEST_PATH_IMAGE099
(ii) a The error of the ith output at the receiving end is expressed as
Figure 19833DEST_PATH_IMAGE100
；
Figure 979698DEST_PATH_IMAGE101
Representing a conjugate transpose.
S3, constructing an adaptive filter and converting the column vector
Figure 568943DEST_PATH_IMAGE102
As an input to the transversal filter, a filter is provided,
Figure 348680DEST_PATH_IMAGE103
as the transversal filter tap coefficients,
Figure 743889DEST_PATH_IMAGE095
as the desired signal, the output of the transversal filter
Figure 745212DEST_PATH_IMAGE091
And simplifying the nonlinear structure of the equalizer into a linear filtering structure for the user information to be acquired.
S4, according to the minimum mean square error rule, the expected signal is transmitted
Figure 567675DEST_PATH_IMAGE095
By using
Figure 834708DEST_PATH_IMAGE104
Expressed, the optimal solution for the equalizer is expressed as:
Figure 971291DEST_PATH_IMAGE032
the optimal solution of the equalizer is expressed by Wiener-Holf equation as:
Figure 640170DEST_PATH_IMAGE033
wherein the content of the first and second substances,
Figure 633534DEST_PATH_IMAGE105
，
Figure 73349DEST_PATH_IMAGE106
representing a conjugate operation.
S5, solving the solution by a conjugate gradient algorithm
Figure 75940DEST_PATH_IMAGE107
And completing the design of the self-adaptive equalizer to ensure that the equalized overall channel is an identity matrix or a switching matrix.
Data model
As shown in fig. 1, if the base station has M antennas and the terminal has N antennas, the signal transmitted by the base station antennas can be represented as:
Figure 599325DEST_PATH_IMAGE108
（1）
likewise, the terminal receiving signal can be expressed as:
Figure 701273DEST_PATH_IMAGE109
（2）
considering the downlink, i.e. base station to terminal transmission scenario, the wideband MIMO wireless channel can be expressed as:
Figure 942899DEST_PATH_IMAGE110
（3）
in the formula (I), the compound is shown in the specification,
Figure 483602DEST_PATH_IMAGE111
is as followslChannel transfer matrix for a strip path:
Figure 48444DEST_PATH_IMAGE112
（4）
in the formula (I), the compound is shown in the specification,
Figure 649190DEST_PATH_IMAGE113
is the first to represent the transmitting endiRoot antenna to receiving endjBetween the root antennaslThe channel gain of the strip path is,Lindicating the number of resolvable multipaths. Thus receiving the signal
Figure 112532DEST_PATH_IMAGE114
And transmit the signal
Figure 456926DEST_PATH_IMAGE115
The relationship between them is:
Figure 627007DEST_PATH_IMAGE116
（5）
then the received signal after adding the equalizer can be expressed as:
Figure 398654DEST_PATH_IMAGE117
（6）
wherein G represents the overall channel after equalization, i.e.
Figure 349292DEST_PATH_IMAGE118
，
Figure 920213DEST_PATH_IMAGE119
Representing the equalizer coefficients, the objective of the equalization at the receiving end is to make the equalized overall channel an identity matrix or a switching matrix.
Two, MIMO channel simulation
As shown in fig. 2, the spatial channels can be obtained by correlation matrix of transmitting and receiving ends, independent impact fading response of each channel and power delay spectrum estimation of the channel. The premise is that all resolvable paths of the channel are independent and each resolvable path has an independent spatial characterization parameter.
It has been theoretically demonstrated that, given some correlation of the MIMO channel, the channel transmission coefficient in equation (4) can be simulated by equation (7):
Figure 272697DEST_PATH_IMAGE120
（7）
in the formula (I), the compound is shown in the specification,
Figure 215245DEST_PATH_IMAGE121
；
Figure 590863DEST_PATH_IMAGE051
is defined in the power delay profilelPower of each resolvable path;
Figure 277059DEST_PATH_IMAGE052
is that
Figure 484050DEST_PATH_IMAGE122
By a transmit-side correlation matrix
Figure 784450DEST_PATH_IMAGE123
Correlation matrix with receiving end
Figure 709681DEST_PATH_IMAGE124
Obtained as a Kroneckor product, i.e.
Figure 933989DEST_PATH_IMAGE125
So as to obtain a spatial correlation matrix
Figure 261065DEST_PATH_IMAGE126
The matrix Γ may be subjected to Cholesky decomposition;
Figure 217519DEST_PATH_IMAGE127
each of which
Figure 630046DEST_PATH_IMAGE128
All are mutually independent small-scale fading, and the vector a can be generated by a simulation method of a single antenna channel.
MMSE equalization technique
As shown in fig. 3, the overall structure of the equalizer, for simplicity, only the filter portions of the feedforward and feedback corresponding to the ith output of the equalizer are considered.
In fig. 3, the inputs to the DFE equalizer are:
Figure 658045DEST_PATH_IMAGE130
the ith output is expressed as:
Figure 525114DEST_PATH_IMAGE131
（8）
or written in vector form:
Figure 980366DEST_PATH_IMAGE132
(9)
by defining the variables:
Figure 614609DEST_PATH_IMAGE098
(10)
the error at the ith output of the DFE filter is:
Figure 118403DEST_PATH_IMAGE133
(11)
substituting the definition of the data variable into the above equation yields:
Figure 420071DEST_PATH_IMAGE100
(12)
further, an adaptive filter model as shown in FIG. 4 can be constructed by using the column vectors
Figure 46225DEST_PATH_IMAGE102
As input to the filter, column vectors
Figure 354715DEST_PATH_IMAGE103
The elements in (b) are considered as transversal filter tap coefficients,
Figure 724517DEST_PATH_IMAGE095
output of the filter, viewed as the desired signal
Figure 880691DEST_PATH_IMAGE091
I.e. the user information to be acquired. Therefore, the nonlinear structure of the DFE is simplified into a linear filtering structure, and the design problem of the equalizer of the MIMO system is also translated into the design problem of the optimal filter.
According to the MMSE rule, the desired signal
Figure 677746DEST_PATH_IMAGE095
By using
Figure 224265DEST_PATH_IMAGE104
It is shown that the MMSE solution of the MIMO system equalizer is:
Figure 132178DEST_PATH_IMAGE134
Figure 142860DEST_PATH_IMAGE135
（12）
the solution to this minimum problem can be expressed as the Wiener-Holf equation:
Figure 799231DEST_PATH_IMAGE136
（13）
wherein the content of the first and second substances,
Figure 895363DEST_PATH_IMAGE105
this equation can be solved optimally by the CG algorithm.
Four, CG algorithm
To make the equalizer adaptive, an iterative solution in equation (13) is required
Figure 606967DEST_PATH_IMAGE107
The traditional adaptive filter algorithm can be adopted, and the algorithm comprises an RLS algorithm and an LMS algorithm. But both algorithms require estimation
Figure 409838DEST_PATH_IMAGE137
If estimated
Figure 548695DEST_PATH_IMAGE137
The loss of positive definite characteristics can also result in the algorithm not converging, and the CG algorithm does not need to calculate
Figure 132124DEST_PATH_IMAGE137
Thus avoiding this problem. The CG algorithm has faster convergence speed compared with the LMS algorithm and smaller operation amount compared with the RLS algorithm, and provides an adaptive algorithm with compromise between convergence speed and operation complexity.
The CG algorithm after adaptation according to the previous equalizer structure is as follows:
Figure 834369DEST_PATH_IMAGE138
（14）
Figure 554063DEST_PATH_IMAGE139
（15）
Figure 863822DEST_PATH_IMAGE140
（16）
Figure 934546DEST_PATH_IMAGE141
（17）
Figure 925636DEST_PATH_IMAGE142
（18）
in the CG algorithm, the cost function used is:
Figure 765416DEST_PATH_IMAGE143
（19）
and in the algorithm implementation process, by adopting an exponential decay data window when calculating R and b:
Figure 246076DEST_PATH_IMAGE144
Figure DEST_PATH_IMAGE145
（20）
the filter coefficient of each iteration can be updated, and the calculation amount is reduced to a great extent.
As shown in fig. 5, the simulation result is that a rayleigh channel is simulated by MATLAB, and when the information source uses BPSK, QPSK, and 8PSK, the 2 × 2MIMO system achieves a good effect of balanced reception, and can effectively reduce the error rate and improve the reliability of communication, and it can be known from the figure that the error rate decreases with the increase of the signal-to-noise ratio and increases with the increase of the modulation order.
The above is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above-mentioned embodiments, and all technical solutions belonging to the idea of the present invention belong to the protection scope of the present invention. It should be noted that modifications and embellishments within the scope of the invention may be made by those skilled in the art without departing from the principle of the invention.

Claims (4)

1. A multi-antenna equalization receiving method for high-speed video communication is characterized in that a base station is provided with M antennas, a terminal is provided with N antennas, and signals transmitted by the base station antennas are represented as follows:
Figure 503470DEST_PATH_IMAGE001
the terminal receives the signal as:
Figure 477242DEST_PATH_IMAGE002
the wideband MIMO wireless channel is represented as
Figure 103396DEST_PATH_IMAGE003
，
Figure 224935DEST_PATH_IMAGE004
Representing a transpose; receiving a signal
Figure 283152DEST_PATH_IMAGE005
And transmit the signal
Figure 439327DEST_PATH_IMAGE006
The relationship between them is:
Figure 236382DEST_PATH_IMAGE007
the received signal after adding the equalizer is expressed as:
Figure 845218DEST_PATH_IMAGE008
(ii) a G denotes the equalized overall channel, i.e.
Figure 690814DEST_PATH_IMAGE009
，
Figure 701495DEST_PATH_IMAGE010
It is shown that the equalizer,
Figure 669451DEST_PATH_IMAGE011
representing time delay and representing convolution operation;
the multi-antenna equalization receiving method comprises the following steps:
s1, obtaining the equalized second signal of the equalizeriAn output
Figure 952534DEST_PATH_IMAGE012
：
Figure DEST_PATH_IMAGE013
In the formula (I), the compound is shown in the specification,
Figure 664138DEST_PATH_IMAGE014
、
Figure 732588DEST_PATH_IMAGE015
respectively a feedforward coefficient and a feedback coefficient output by the equalizer;
Figure 871446DEST_PATH_IMAGE016
、
Figure 189294DEST_PATH_IMAGE017
respectively before equalization of the equalizerjAn input and aiThe output of the first and second processors is,
Figure 704589DEST_PATH_IMAGE018
，
Figure 375349DEST_PATH_IMAGE019
；
s2, defining variables:
Figure 685107DEST_PATH_IMAGE020
respectively representing a signal matrix and a coefficient matrix,
Figure 490252DEST_PATH_IMAGE021
and
Figure 481342DEST_PATH_IMAGE022
respectively represent
Figure 321122DEST_PATH_IMAGE023
And
Figure 801782DEST_PATH_IMAGE024
i.e., a feed-forward coefficient matrix and a feedback coefficient matrix,
Figure 359802DEST_PATH_IMAGE025
representing a common set of feedforward and feedback coefficient matricesA coefficient matrix of the block; will be the first of the equalizeriAn output
Figure 138271DEST_PATH_IMAGE012
Is converted into
Figure 98137DEST_PATH_IMAGE026
(ii) a At the receiving endiThe error of each output is expressed as
Figure 749698DEST_PATH_IMAGE027
；
Figure 467119DEST_PATH_IMAGE028
Represents a conjugate transpose;
s3, constructing an adaptive filter and converting the column vector
Figure 862328DEST_PATH_IMAGE029
As an input to the transversal filter, a filter is provided,
Figure 676700DEST_PATH_IMAGE030
as the transversal filter tap coefficients,
Figure 499163DEST_PATH_IMAGE017
as the desired signal, the output of the transversal filter
Figure 454611DEST_PATH_IMAGE012
Simplifying the nonlinear structure of the equalizer into a linear filtering structure for the user information to be acquired;
s4, according to the minimum mean square error rule, the expected signal is transmitted
Figure 653512DEST_PATH_IMAGE017
By using
Figure 322390DEST_PATH_IMAGE031
Expressed, the optimal solution for the equalizer is expressed as:
Figure 253437DEST_PATH_IMAGE032
the optimal solution of the equalizer is expressed by Wiener-Holf equation as:
Figure 7767DEST_PATH_IMAGE033
wherein the content of the first and second substances,
Figure 10358DEST_PATH_IMAGE034
，
Figure 533743DEST_PATH_IMAGE035
represents a conjugate operation;
s5, solving the solution by a conjugate gradient algorithm
Figure 884959DEST_PATH_IMAGE036
And completing the design of the self-adaptive equalizer to ensure that the equalized overall channel is an identity matrix or a switching matrix.
2. The multiple antenna equalization reception method for high speed video communication according to claim 1, wherein the wideband MIMO wireless channel is represented as:
Figure 126584DEST_PATH_IMAGE037
in the formula (I), the compound is shown in the specification,
Figure 667287DEST_PATH_IMAGE038
is the firstlThe delay of the strip path is such that,
Figure 982862DEST_PATH_IMAGE039
the function of the impact is expressed as,
Figure 583607DEST_PATH_IMAGE040
is the firstlThe time delay of the strip path is,
Figure 46950DEST_PATH_IMAGE041
is as followslChannel transfer matrix for a strip path:
Figure 82689DEST_PATH_IMAGE042
in the formula (I), the compound is shown in the specification,
Figure 315087DEST_PATH_IMAGE043
is the first to represent the transmitting end
Figure 86734DEST_PATH_IMAGE044
Root antenna to receiving end
Figure 37372DEST_PATH_IMAGE045
Between the root antennaslThe channel gain of the strip path is,
Figure 857561DEST_PATH_IMAGE046
indicating the number of resolvable multipaths,
Figure 210045DEST_PATH_IMAGE047
，
Figure 152593DEST_PATH_IMAGE048
。
3. the multiple antenna equalization reception method for high speed video communication according to claim 2, characterized in that on the basis of correlation of a given MIMO channel, channel transmission coefficients are simulated by the following formula:
Figure 777478DEST_PATH_IMAGE050
in the formula (I), the compound is shown in the specification,
Figure 463674DEST_PATH_IMAGE051
；
Figure 670665DEST_PATH_IMAGE052
is defined in the power delay profilelPower of each resolvable path;
Figure 721797DEST_PATH_IMAGE053
is that
Figure 647028DEST_PATH_IMAGE054
By a transmit-side correlation matrix
Figure 871336DEST_PATH_IMAGE055
Correlation matrix with receiving end
Figure 198412DEST_PATH_IMAGE056
Obtained as a Kroneckor product, i.e.
Figure 905599DEST_PATH_IMAGE057
；
Figure 318126DEST_PATH_IMAGE058
Each of which
Figure 346125DEST_PATH_IMAGE059
Representing independent small scale fading in each path, generating vector a by simulation method of single antenna channel, sharing M × N different paths from transmitting antenna to receiving antenna,
Figure 465391DEST_PATH_IMAGE060
。
4. the multiple antenna equalization reception method for high speed video communication according to claim 1, whereinIn step S5, the solution is iteratively solved by a conjugate gradient algorithm
Figure 920643DEST_PATH_IMAGE036
Comprises the following steps:
according to the structure of the equalizer, iteratively updating the filter coefficient by adopting an adjusted conjugate gradient algorithm until convergence; the adjusted conjugate gradient algorithm is as follows:
Figure 554886DEST_PATH_IMAGE061
Figure 120997DEST_PATH_IMAGE062
Figure 609616DEST_PATH_IMAGE063
Figure 235769DEST_PATH_IMAGE064
Figure 357309DEST_PATH_IMAGE065
；
wherein the content of the first and second substances,
Figure 664794DEST_PATH_IMAGE066
taking 1, the step length is adjusted,
Figure 820969DEST_PATH_IMAGE067
is an input vector
Figure 618023DEST_PATH_IMAGE068
The correlation matrix of (a) is calculated,
Figure 226859DEST_PATH_IMAGE069
which represents a direction vector of the light beam,
Figure 820258DEST_PATH_IMAGE070
the step size is represented as a function of time,
Figure 830939DEST_PATH_IMAGE071
which represents the vector of the residual error,
Figure 798895DEST_PATH_IMAGE072
is orthogonal
Figure 832711DEST_PATH_IMAGE069
The vector of the vector is then calculated,
Figure 544315DEST_PATH_IMAGE073
representing the forgetting factor corresponding to the feedback coefficient of the jth receiving antenna,
Figure 409502DEST_PATH_IMAGE031
representing a desired value of the output;
the cost function used is:
Figure 735310DEST_PATH_IMAGE074
；
wherein the content of the first and second substances,brepresenting an association vector between the input data and the expected value;
calculated using exponentially decaying data windows
Figure 318739DEST_PATH_IMAGE067
And
Figure 834033DEST_PATH_IMAGE075
：
Figure 553728DEST_PATH_IMAGE076
Figure 801170DEST_PATH_IMAGE077
wherein the content of the first and second substances,
Figure 871894DEST_PATH_IMAGE078
expressing the first in solving the feedback coefficient
Figure 551399DEST_PATH_IMAGE079
And the forgetting factor corresponding to the individual expression.
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