CN111181607A - Physical layer coding optimization antenna selection method based on soft message selection forwarding - Google Patents

Physical layer coding optimization antenna selection method based on soft message selection forwarding Download PDF

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CN111181607A
CN111181607A CN202010021643.XA CN202010021643A CN111181607A CN 111181607 A CN111181607 A CN 111181607A CN 202010021643 A CN202010021643 A CN 202010021643A CN 111181607 A CN111181607 A CN 111181607A
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relay node
antenna
signal
antenna set
mutual information
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CN111181607B (en
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包建荣
林昀轩
刘超
邸晓飞
姜斌
栾慎吉
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Hangzhou Dianzi University
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    • 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
    • H04B—TRANSMISSION
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    • H04B17/336—Signal-to-interference ratio [SIR] or carrier-to-interference ratio [CIR]
    • 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
    • H04B7/0426—Power distribution
    • 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
    • H04B7/0456—Selection of precoding matrices or codebooks, e.g. using matrices antenna weighting
    • H04B7/046—Selection of precoding matrices or codebooks, e.g. using matrices antenna weighting taking physical layer constraints into account

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Abstract

A physical layer coding optimization antenna selection method based on soft message forwarding selection. The invention discloses a method for optimizing antenna selection by physical layer coding, which comprises the following steps: s1, transmitting a signal to be transmitted to a relay node through a channel; s2, the relay node signal adopts a sum-difference linear transformation method to obtain a sum signal and a difference signal; s3, the relay node processes distortion introduced by a channel in the obtained sum signal and difference signal by adopting a zero forcing detection method to obtain a signal; s4, screening signals by the relay node, and mapping the signals into a log-likelihood form by adopting a log-likelihood ratio mapping method; s5, deleting a part of antennas by the relay node based on the mutual information antenna set pre-selection method to obtain an initial antenna set; s6, selecting a required antenna set by the relay node based on an antenna selection method of a maximum and minimum mutual information criterion, and averagely distributing transmitting power to the selected antenna; s7, the relay node sends the signal broadcast obtained by mapping to the user node through the selected antenna; and S8, the user node decodes the received signal by adopting a decoding mode based on threshold judgment to obtain a final result.

Description

Physical layer coding optimization antenna selection method based on soft message selection forwarding
Technical Field
The invention relates to the technical field of digital communication engineering, in particular to a physical layer coding optimization antenna selection method based on soft message forwarding selection.
Background
In the prior art, the PNC is mainly studied based on an equidistant model, i.e. the distances between two source nodes and a relay node are equal. However, in actual wireless communication, distances between two source nodes and a relay node are not always equal, which causes Near-Far effect (NFE) (see "y.huang, t.tan, s.pen and c.cheng.a. malandactive power allocation for physical layer network coding in wireless networks [ J ].2013 selective International Conference on Complex, Intelligent, and software Intelligent Systems, Taichung,2013, pp.320-324."). Moreover, even if the distances between the two source nodes and the relay node are equal, due to the influences of path loss, shadow fading, multipath fading and the like, the strengths of signals received by the relay node from the two source nodes are different, so that the Bit Error Rate (BER) performance of the system is reduced. Therefore, power allocation during both Multiple Access (MA) and Broadcast (BC) phases is critical. Currently, research on PNC power allocation mainly takes BER, outage probability, and the like as objective functions. Meanwhile, the method is based on two most main cooperative methods, namely Amplify-and-Forward (AF) and Decode-and-Forward (DF) cooperation (see Q.Yu, Y.Li, W.Meng and W.X.Uniquely decoded codes in wireless cooperative communications [ J ]. IEEESystems journal ]. The Selective Soft-Message-Forward (SSMF) cooperation fully combines the advantages of AF and DF cooperation, and can further improve the system performance. But at present, no physical layer coding power allocation research based on SSMF cooperation exists.
Therefore, the present invention provides an optimal antenna selection and Adaptive Power Allocation (APA) method based on the Max-Min Mutual Information (MMMI) criterion to solve the above problems.
Disclosure of Invention
The invention aims to provide a physical layer coding optimization antenna selection method based on soft message forwarding selection, which is convenient for network base stations in various areas to apply a large-scale antenna transmission technology and has better error rate performance and lower calculation complexity compared with the existing physical layer coding method. Therefore, the method has good practical value and can be effectively used for the next generation wireless communication such as the fifth generation mobile communication.
In order to achieve the purpose, the invention adopts the following technical scheme:
a physical layer coding optimization antenna selection method based on soft message forwarding selection comprises the following steps:
s1. user node SiSignal x to be transmittediTransmitting to a relay node R through a channel;
s2, the relay node R receives a signal xiObtaining a sum signal and a difference signal by adopting a sum-difference linear transformation method;
s3, the relay node R processes distortion introduced by a channel in the obtained sum signal and difference signal by adopting a zero forcing detection method to obtain a processed signal
Figure BDA0002361016960000022
S4, the relay node R screens the obtained processed signals
Figure BDA0002361016960000023
Mapping the screened signals into a log-likelihood form by adopting a log-likelihood ratio mapping method;
s5, deleting a part of antennas by the relay node R based on the mutual information antenna set pre-selection method to obtain an initial antenna set;
s6, the relay node R selects a required antenna set from the obtained initial antenna set based on an antenna selection method of a maximum and minimum mutual information criterion, and distributes transmitting power to the selected antenna set in the required antenna set averagely;
s7, the relay node R sends the signal broadcast obtained by mapping to the user node S through the selected antenna in the required antenna seti；
S8, the user node SiAnd decoding the received signal by adopting a decoding mode based on threshold judgment to obtain a final result.
Further, in the step S1, the user node SiComprising S1And S2(ii) a The signal x to be transmittediIncluding x1And x2。
Further, in step S2, the relay node R receives the signal xiExpressed as:
Figure BDA0002361016960000021
Figure BDA0002361016960000031
wherein the content of the first and second substances,
Figure BDA0002361016960000032
respectively representing signals received by the 1 st and 2 nd sub antennas of the relay node R;
Figure BDA0002361016960000033
Figure BDA0002361016960000034
respectively representing user nodes S1、S2The transmit power of (a); h is11,1、h12,1、h21,1、h22,1Respectively representing user nodes S1、S2To the relay node RthChannel coefficients of links between 1 pair of antennas and 2 nd pair of antennas; n is1,1、n2,1Respectively representing additive white Gaussian noise at the 1 st pair of antennas and the 2 nd pair of antennas of the relay node R; x is the number of1、x2Respectively representing user nodes S1、S2The transmitted signal;
in step S2, the signal received by the relay node R
Figure BDA0002361016960000035
Expressed in matrix form as:
XR＝HX+N
Figure BDA0002361016960000036
wherein H, X, N represents a matrix or vector;
the step S2 further includes the relay node R performing sum-difference linear transformation on the received signal to obtain a sum signal and a difference signal, and detecting the obtained sum signal and difference signal, where the received signal of the relay node R is represented as:
Figure BDA0002361016960000037
Figure BDA0002361016960000038
Figure BDA0002361016960000039
wherein the content of the first and second substances,
Figure BDA00023610169600000310
a representation sum signal;
Figure BDA00023610169600000311
representing a difference signal.
Further, in step S3, the relay node R corrects the obtained sum signal and difference signal by using a zero-forcing detection method, where the distortion introduced by the channel is expressed as:
Figure BDA00023610169600000312
wherein the content of the first and second substances,
Figure BDA00023610169600000313
an equalization matrix representing a zero forcing detection method;
Figure BDA00023610169600000314
to represent
Figure BDA00023610169600000315
The conjugate transpose matrix of (a);
Figure BDA00023610169600000316
to represent
Figure BDA00023610169600000317
The inverse matrix of (d);
in step S3, a corrected signal is obtained
Figure BDA00023610169600000318
Expressed as:
Figure BDA00023610169600000319
Figure BDA00023610169600000320
wherein the content of the first and second substances,
Figure BDA0002361016960000041
represents the corrected signal;
Figure BDA0002361016960000042
respectively representing the noise at the 1 st and 2 nd sub-antennas amplified by the zero forcing detection method.
Further, in step S4, the selected signal is mapped into a log-likelihood format by using a log-likelihood ratio mapping method, and the log-likelihood format is expressed as:
Figure BDA0002361016960000043
wherein the content of the first and second substances,
Figure BDA0002361016960000044
representing a signal variable x1、x2Exclusive or of;
Figure BDA0002361016960000045
represents the variance;
Figure BDA0002361016960000046
Figure BDA0002361016960000047
wherein the content of the first and second substances,
Figure BDA0002361016960000048
the formula is arranged as follows:
Figure BDA0002361016960000049
Figure BDA0002361016960000051
in step S4, the method further includes adding a 1-bit flag to the mapped data, which is expressed as:
Figure BDA0002361016960000052
where sign denotes a flag.
Further, the step S5 includes:
s51, the relay node R obtains the source node of each antenna by adopting a channel estimation methodPoint S1And S2The channel state information of (a);
s52, judging that the kth antenna of the relay node R reaches the source node S1And S2If the channel state information meets the deletion condition, the relay node R adds the kth antenna into the initial antenna set; wherein the deletion condition is expressed as:
Figure BDA0002361016960000053
Figure BDA0002361016960000054
wherein, N represents the number of antennas owned by the relay node R, and is a positive integer; h isij,2Indicating the relay node R ith antenna to the source node SjThe channel coefficients of the link between.
Further, the step S6 includes:
s61, when the relay node R calculates that all antennas in the initial antenna set participate in forwarding, the source node S1And S2The obtained mutual information quantity;
s62, calculating a source node S by a relay node R1And S2Initial minimum mutual information amount;
s63, the relay node R selects antennas from the initial antenna set one by one to delete the antennas, a new antenna set is obtained, and a source node S of the new antenna set is calculated1And S2Minimum mutual information amount of (a);
s64, judging whether the minimum mutual information quantity of the new antenna set is larger than or equal to the initial antenna set, if so, taking the new antenna set and the minimum mutual information quantity as the initial antenna set and the initial mutual information quantity, and executing the step S63; if not, the execution is finished.
Further, the mutual information amount obtained in step S61 is represented as:
Figure BDA0002361016960000061
Figure BDA0002361016960000062
wherein the content of the first and second substances,
Figure BDA0002361016960000063
and
Figure BDA0002361016960000064
respectively representing source nodes S1And S2In the antenna set RiMutual information amount obtained under the condition;
Figure BDA0002361016960000065
representing the transmitting power of the jth antenna of the relay node R; h isij,2Indicating the relay node R ith antenna to the source node SjChannel coefficients of the inter-link; n' represents the number of antennas in the initial antenna set;
Figure BDA0002361016960000066
representing a source node SiVariance of white gaussian noise; when the antennas in the initial antenna set are all participating in the retransmission,
Figure BDA0002361016960000067
wherein, PrRepresenting the total transmission power of the relay node R;
further, in the step S62, a source node S is calculated1And S2The initial minimum mutual information amount is expressed as:
Figure BDA0002361016960000068
wherein, Imin,iRepresenting a source node S1And S2In the antenna set RiMinimum mutual information amount obtained under the condition;
the step S63 is specifically to delete the antenna a from the initial antenna set1Obtaining a new antenna set
Figure BDA0002361016960000069
Wherein
Figure BDA00023610169600000610
Indicating the deletion of antenna a from the original set of antennasiObtaining a new antenna set; new antenna source node S1And S2The minimum mutual information amount can be expressed as:
Figure BDA00023610169600000611
wherein the content of the first and second substances,
Figure BDA00023610169600000612
Figure BDA00023610169600000613
Figure BDA00023610169600000614
repeatedly executing to obtain the minimum mutual information quantity of the new antenna set to obtain N' minimum mutual information quantities;
selecting the largest minimum mutual information quantity from the N' minimum mutual information quantities as the minimum mutual information quantity after deleting 1 antenna, wherein the minimum mutual information quantity is expressed as follows:
Figure BDA00023610169600000615
in step S64, it is determined whether the minimum mutual information amount of the new antenna set is greater than or equal to the initial antenna set, and the determination is represented as:
Imin,1/Imin,0≥1。
compared with the prior art, the invention provides an optimized antenna selection method. In the broadcasting stage, the relay node deletes part of antennas from all antennas to obtain an initial antenna set by taking the mutual information quantity of the two source nodes not to be reduced in the stage as a deletion standard. Then, the relay node takes the minimum mutual information quantity of the two source nodes in the time slot as a target function, selects an optimal antenna set from the initial antenna set, and averagely distributes the transmitting power to the antennas in the optimal antenna set. The invention facilitates the application of large-scale antenna transmission technology by each area network base station, and simultaneously has better error rate performance and lower computation complexity compared with the prior physical layer coding method. Therefore, the method has good practical value and can be effectively used for the next generation wireless communication such as the fifth generation mobile communication.
Drawings
Fig. 1 is a flowchart of a method for selecting an antenna based on physical layer coding optimization for soft message forwarding according to an embodiment;
fig. 2 is a model of a MIMO two-way relay network system according to a second embodiment;
FIG. 3 is a comparison of end-to-end Bit Error Rate (BER) performance for different physical layer codes provided by the second embodiment;
FIG. 4 is a graph of end-to-end throughput comparison for different physical layer coding schemes provided in example two;
FIG. 5 is a second embodiment of a providing source node S2The distance between the relay node and the relay node influences the transmitting power of each antenna of the relay node;
FIG. 6 is a comparison of the front and back end-to-end BER performance using the optimized antenna selection method under different numbers of antennas provided in example two;
FIG. 7 is a comparison of end-to-end BER performance before and after the antenna set pre-selection algorithm provided in example two;
fig. 8 is the average number of remaining antennas after the antenna set pre-selection algorithm is adopted under different signal-to-noise ratios provided by the second embodiment.
Detailed Description
The embodiments of the present invention are described below with reference to specific embodiments, and other advantages and effects of the present invention will be easily understood by those skilled in the art from the disclosure of the present specification. The invention is capable of other and different embodiments and of being practiced or of being carried out in various ways, and its several details are capable of modification in various respects, all without departing from the spirit and scope of the present invention. It is to be noted that the features in the following embodiments and examples may be combined with each other without conflict.
The invention aims to provide a physical layer coding optimization antenna selection method based on soft message forwarding selection aiming at the defects of the prior art.
Example one
The present embodiment provides a method for selecting an antenna based on physical layer coding optimization for soft message forwarding, as shown in fig. 1. The method comprises the following steps:
s1. user node SiSignal x to be transmittediTransmitting to a relay node R through a channel;
s2, the relay node R receives a signal xiObtaining a sum signal and a difference signal by adopting a sum-difference linear transformation method;
s3, the relay node R processes distortion introduced by a channel in the obtained sum signal and difference signal by adopting a zero forcing detection method to obtain a processed signal
Figure BDA0002361016960000081
S4, the relay node R screens the obtained processed signals
Figure BDA0002361016960000082
Mapping the screened signals into a log-likelihood form by adopting a log-likelihood ratio mapping method;
s5, deleting a part of antennas by the relay node R based on the mutual information antenna set pre-selection method to obtain an initial antenna set;
s6, the relay node R selects a required antenna set from the obtained initial antenna set based on an antenna selection method of a maximum and minimum mutual information criterion, and distributes transmitting power to the selected antenna set in the required antenna set averagely;
s7, the relay node R sends the signal broadcast obtained by mapping to the user node S through the selected antenna in the required antenna seti；
S8, the user node SiAnd decoding the received signal by adopting a decoding mode based on threshold judgment to obtain a final result.
In the embodiment, firstly, two user nodes S are in the Multiple Access (MA) stage1And S2Simultaneously transmitting a signal x1And x2Is transmitted to the relay node R via a channel, and x1And x2Is an integer taking the value +1 or-1.
Then, the relay node R obtains the sum signal of two paths of signals by using a sum-difference linear transformation method "
Figure BDA0002361016960000083
Sum "difference signal"
Figure BDA0002361016960000084
Wherein the content of the first and second substances,
Figure BDA0002361016960000085
and
Figure BDA0002361016960000086
are all integers, and
Figure BDA0002361016960000087
the relay node R then employs a zero forcing detection (ZF) method to reduce the signal
Figure BDA0002361016960000088
And
Figure BDA0002361016960000089
in which the distortion introduced by the channel is obtained as a processed signal
Figure BDA00023610169600000810
And
Figure BDA00023610169600000811
in the Broadcast (BC) stage, the relay node deletes part of antennas from all antennas to obtain an initial antenna set by taking the mutual information quantity of the two source nodes not to be reduced in the stage as a deletion standard. Mutual information is a useful information metric in information theory, which is the unsuitability of a random variable to be reduced by the knowledge of another random variable. Then, the relay node takes the minimum mutual information quantity of the two source nodes in the time slot as a target function, selects an optimal antenna set from the initial antenna set, and averagely distributes the transmitting power to the antennas in the optimal antenna set.
Note that, the zero forcing detection (ZF) method:
the ZF method is a detector commonly used in MIMO systems, and its core idea is to eliminate interference between signals transmitted from different antennas at the receiving end through linear transformation. The signal received by a receiving end in the MIMO system is represented as the following form:
y＝h1x1+h2x2+…+hkxk+n (1)
wherein, y is a complex number and represents a signal received by a receiving end; x is the number ofiThe complex number represents the signal sent by the ith user; h isiThe channel coefficient of the link from the ith user to the receiving end is expressed as a complex number; k is a positive integer and represents the number of users in the MIMO system; n is complex number, which represents the additive white Gaussian noise of the receiving end. Where i ∈ (1, 2, … k).
To recover x at the receiving endiWhile excluding interference from other signals, the ZF method uses a vector wiInner product with y, where wiThe following conditions are satisfied:
Figure BDA0002361016960000091
in step S1, the user node SiSignal x to be transmittediTransmitted to the relay node R via the channel.
User node SiComprising S1And S2(ii) a Signal x to be transmittediIncluding x1And x2。
In the Multiple Access (MA) phase, two user nodes S1And S2Simultaneously transmitting a signal x1And x2And transmitted to the relay node R via a channel.
In step S2, the relay node R will receive the signal xiAnd obtaining a sum signal and a difference signal by adopting a sum-difference linear transformation method.
The relay node R receives the signal xiExpressed as:
Figure BDA0002361016960000092
Figure BDA0002361016960000093
wherein the content of the first and second substances,
Figure BDA0002361016960000094
respectively representing the signals received by the 1 st and 2 nd sub-antennas of the relay node R,
Figure BDA0002361016960000095
Figure BDA0002361016960000096
is a plurality;
Figure BDA0002361016960000097
respectively representing user nodes S1、S2The transmission power of the antenna is set to be,
Figure BDA0002361016960000098
a real number greater than 0; h is11,1、h12,1、h21,1、h22,1Respectively representing user nodes S1、S2The channel coefficient of the link between the 1 st and 2 nd antennas of the relay node R obeys a mean value of 0 and a variance of 0
Figure BDA0002361016960000101
Complex gaussian distribution of (a); n is1,1、n2,1Respectively represents the Additive White Gaussian Noise (AWGN) at the 1 st and 2 nd secondary antennas of the relay node R1,1、n2,1Is complex, obeys a mean of 0, and has a variance of
Figure BDA0002361016960000102
Complex gaussian distribution of (a); x is the number of1、x2Respectively representing user nodes S1、S2The transmitted signal is modulated by Binary Phase Shift Keying (BPSK).
For convenience of expression, equations (3) and (4) are rewritten in a matrix form:
XR＝HX+N (5)
Figure BDA0002361016960000103
wherein capital letters, such as H, represent a matrix or vector; corresponding lower case letters, e.g. hij,1The element of H on the ith row and jth column is represented, and i and j are natural numbers.
In the embodiment, the relay node R performs sum-difference linear transformation on the received signal to obtain a sum signal of two paths of signals "
Figure BDA0002361016960000104
Sum "difference signal"
Figure BDA0002361016960000105
Of interest to the relay node R is the Network Coding (NC) symbols to be transmitted to the user nodes, rather than the user nodes sending the signal x1And x2The exact value of (c). Therefore, in this embodiment, the relay node R does not independently detect the information streams of the two user nodes, but obtains the sum signal and the difference signal of the two paths of information through sum-difference linear transformation, and then directly detects the sum signal or the difference signal. At this time, the signals received by the antennas of the relay node R may be rewritten as:
Figure BDA0002361016960000106
Figure BDA0002361016960000107
Figure BDA0002361016960000108
wherein the content of the first and second substances,
Figure BDA0002361016960000109
a representation sum signal;
Figure BDA00023610169600001010
representing a difference signal.
In step S3, the relay node R processes the distortion introduced by the channel in the obtained sum signal and difference signal by using a zero-forcing detection method to obtain a processed signal
Figure BDA00023610169600001011
The relay node R adopts a zero forcing detection ZF method to correct
Figure BDA00023610169600001012
There is channel-induced distortion, expressed as:
Figure BDA0002361016960000111
wherein, YRRepresenting a signal matrix processed by a ZF method; xRRepresenting a relay node received signal matrix;
Figure BDA0002361016960000112
representing the channel matrix after the sum and difference linear transformation;
Figure BDA0002361016960000113
an equalization matrix representing a zero forcing detection method;
Figure BDA0002361016960000114
to represent
Figure BDA0002361016960000115
The conjugate transpose matrix of (a);
Figure BDA0002361016960000116
to represent
Figure BDA0002361016960000117
The inverse matrix of (c).
At this time, the signal obtained by the relay node can be expressed as:
Figure BDA0002361016960000118
Figure BDA0002361016960000119
wherein the content of the first and second substances,
Figure BDA00023610169600001110
representing that the received signal of the ith antenna of the relay node after being processed by a ZF method is a complex number; x is the number ofiThe signal is an integer with a value of +1 or-1, represents a signal sent by a user node Si, and is modulated by Binary Phase Shift Keying (BPSK);
Figure BDA00023610169600001111
is complex number, represents the noise at the i-th sub-antenna amplified by zero-forcing detection ZF method in MA stage, and obeys mean value of 0 and variance of
Figure BDA00023610169600001112
Complex gaussian distribution. Wherein i ∈ (1, 2).
In step S4, the relay node R screens the obtained processed signal
Figure BDA00023610169600001113
And mapping the screened signals into a log-likelihood form by a log-likelihood ratio mapping method.
Selection of noise contained in relay node R
Figure BDA00023610169600001114
The minimum processed signal is mapped into LLR form by using log-likelihood ratio (LLR) mapping method。
The reliability degree of the superposed signals received by different antennas of the relay node R is mainly determined by the formula (11) and the formula (12)
Figure BDA00023610169600001115
And (6) determining. Selecting
Figure BDA00023610169600001116
The minimum superposed signal is mapped, so that the Bit Error Rate (BER) performance of the system can be further improved, and the calculation complexity can be reduced. Specifically, the method comprises the following steps:
Figure BDA00023610169600001117
wherein the content of the first and second substances,
Figure BDA00023610169600001118
represents the variance;
Figure BDA00023610169600001119
representing a signal variable x1、x2Exclusive or of;
Figure BDA00023610169600001120
Figure BDA0002361016960000121
Figure BDA0002361016960000122
because of the fact that
Figure BDA0002361016960000123
Therefore, in order to reduce complexity and facilitate waveform processing of the superimposed signal, equations (14) and (15) are organized as follows:
Figure BDA0002361016960000124
Figure BDA0002361016960000125
obtained by the formula (16) and the formula (17)
Figure BDA0002361016960000126
Is mapped as
Figure BDA0002361016960000127
The process of (a) is not the same. Therefore, in order to facilitate the user node to decode the signal by using a decoding method based on Threshold Decision (TD), a 1-bit flag sign needs to be added to the data frame, and the flag is expressed as:
Figure BDA0002361016960000128
in step S5, the relay node R deletes a part of antennas based on the mutual information antenna set pre-selection method, and obtains an initial antenna set.
In the Broadcast (BC) stage, the relay node deletes part of antennas from all antennas to obtain an initial antenna set by using an antenna set pre-selection method based on mutual information. Mutual information is a useful information metric in information theory, which is the unsuitability of a random variable to be reduced by the knowledge of another random variable.
Wherein step S5 includes:
s51, the relay node R obtains the source node S from each antenna by adopting a channel estimation method1And S2The channel state information of (a);
in a Broadcast (BC) stage, a relay node R obtains each antenna to a source node S in the BC stage by utilizing a channel estimation method1And S2The channel state information of (a).
S52, judging that the kth antenna of the relay node R reaches the source node S1And S2If the channel state information meets the deletion condition, the relay node R adds the kth antenna into the initial antenna set; wherein the deletion condition is expressed as:
Figure BDA0002361016960000131
Figure BDA0002361016960000132
wherein, N represents the number of antennas owned by the relay node R, and is a positive integer; h isij,2Indicating the relay node R ith antenna to the source node SjChannel coefficient of the link between hij,2Is a plurality of numbers.
If the k antenna of the relay node reaches the source node S1And S2If the channel state information of (1) satisfies the formula (19) and the formula (20), it does not participate in the forwarding of the BC stage; otherwise the relay node adds it to the initial antenna set.
The initial antenna set obtained by the relay node by adopting the antenna set pre-selection method based on mutual information can be represented as R0＝{a1,a2,...,aN'}. Wherein a isiRepresenting the ith antenna in the initial antenna set; n' is a positive integer representing the number of antennas in the initial antenna set.
Wherein the theoretical basis of the formulas (19) and (20) is as follows:
when the kth antenna in the initial antenna set does not participate in the forwarding in the BC stage, the mutual information amount of the two source nodes may be represented as:
Figure BDA0002361016960000133
Figure BDA0002361016960000134
wherein the content of the first and second substances,
Figure BDA0002361016960000135
the number is positive, which indicates the mutual information quantity of the two source nodes when the kth antenna does not participate in the BC stage forwarding; n is a positive integer and represents the number of antennas owned by the relay node; h isij,2Is complex number, represents the ith antenna of the relay node to the source node in the BC stageSjChannel coefficients of the inter-link;
Figure BDA0002361016960000136
and the positive number represents the transmission power of the jth antenna of the relay node in the BC stage. When the kth antenna is not participating in BC phase forwarding,
Figure BDA0002361016960000141
wherein i is a positive integer, i is more than or equal to 1 and less than or equal to N, and i is not equal to k; prAnd the total transmission power of the relay node in the BC stage is represented as a positive number.
In the mutual information-based antenna set pre-selection method, the deletion of the antenna needs to take the mutual information quantity of two source nodes in the BC stage as a deletion standard without reducing. That is, if
Figure BDA0002361016960000142
And is
Figure BDA0002361016960000143
The kth antenna does not participate in the forwarding of the BC phase. Wherein the content of the first and second substances,
Figure BDA0002361016960000144
Figure BDA0002361016960000145
Figure BDA0002361016960000146
substituting the formula (5) and the formula (7)
Figure BDA0002361016960000147
Obtaining:
Figure BDA0002361016960000148
because log2(1+ x) is a monotonically increasing function, so equation (25) can be rewritten as:
Figure BDA0002361016960000149
equation (19) can be obtained by simplifying equation (26). Similarly, equation (20) can be derived in the same way.
In step S6, the relay node R selects a desired antenna set from the obtained initial antenna set based on the antenna selection method of the maximum-minimum mutual information criterion, and equally distributes the transmission power to the antennas in the selected desired antenna set.
The relay node selects an optimal antenna set from the initial antenna set by using an antenna selection method based on a maximum and minimum mutual information criterion, and distributes transmitting power to the antennas in the optimal antenna set averagely.
Step S6 includes:
s61, when the relay node R calculates that all antennas in the initial antenna set participate in forwarding, the source node S1And S2The obtained mutual information quantity;
Figure BDA00023610169600001410
Figure BDA0002361016960000151
wherein the content of the first and second substances,
Figure BDA0002361016960000152
and
Figure BDA0002361016960000153
respectively representing source nodes S1And S2In the antenna set RiMutual information amount obtained under the condition;
Figure BDA0002361016960000154
representing the transmitting power of the jth antenna of the relay node R; h isij,2Indicating the relay node R ith antenna to the source node SjChannel coefficients of the inter-link; n' represents the number of antennas in the initial antenna set;
Figure BDA0002361016960000155
representing a source node SiVariance of white gaussian noise; when the antennas in the initial antenna set are all participating in the retransmission,
Figure BDA0002361016960000156
wherein, PrRepresenting the total transmit power of the relay node R.
S62, calculating a source node S by a relay node R1And S2Initial minimum mutual information amount;
Figure BDA0002361016960000157
wherein, Imin,iRepresenting a source node S1And S2In the antenna set RiThe minimum mutual information amount obtained under the condition.
S63, the relay node R selects antennas from the initial antenna set one by one to delete the antennas, a new antenna set is obtained, and a source node S of the new antenna set is calculated1And S2Minimum mutual information amount of (a);
to obtain the optimal antenna set, the relay node selects antennas from the initial antenna set one by one for deletion, e.g., deleting antenna a from the initial antenna set1Obtaining a new antenna set R1 1＝{a2,a3,...,aN'Therein of
Figure BDA0002361016960000158
Indicating the deletion of antenna a from the original set of antennasiObtaining a new antenna set; new antenna source node S1And S2The minimum mutual information amount can be expressed as:
Figure BDA0002361016960000159
wherein the content of the first and second substances,
Figure BDA00023610169600001510
Figure BDA00023610169600001511
Figure BDA00023610169600001512
repeating the above operations to obtain N' minimum mutual information quantities; then, the largest one is selected as the minimum mutual information amount after deleting 1 antenna, and the maximum mutual information amount is expressed as:
Figure BDA00023610169600001513
s64, judging whether the minimum mutual information quantity of the new antenna set is larger than or equal to the initial antenna set, if so, taking the new antenna set and the minimum mutual information quantity as the initial antenna set and the initial mutual information quantity, and executing the step S63; if not, the execution is finished.
Imin,1/Imin,0≥1 (34)
If the formula (33) satisfies the condition in the formula (34), the new antenna set and the minimum mutual information amount at this time are used as the initial antenna set and the initial mutual information amount, and the step S63 is repeated until the formula (33) no longer satisfies the condition in the formula (34) or only one antenna remains in the new antenna set at this time.
In step S7, the relay node R sends the mapped signal broadcast to the user node S via the selected antenna in the desired antenna seti。
In the Broadcast (BC) stage, the relay node sends the mapped signal broadcast back to the user node S through the selected antenna in the required antenna set1And S2。
In step S8, the user node SiAnd decoding the received signal by adopting a decoding mode based on threshold judgment to obtain a final result.
Compared with the prior art, the embodiment provides an optimized antenna selection method. In the broadcasting stage, the relay node deletes part of antennas from all antennas to obtain an initial antenna set by taking the mutual information quantity of the two source nodes not to be reduced in the stage as a deletion standard. Then, the relay node takes the minimum mutual information quantity of the two source nodes in the time slot as a target function, selects an optimal antenna set from the initial antenna set, and averagely distributes the transmitting power to the antennas in the optimal antenna set. The embodiment facilitates the application of a large-scale antenna transmission technology by each area network base station, and simultaneously has better error rate performance and lower computational complexity compared with the existing physical layer coding method. Therefore, the method has good practical value and can be effectively used for the next generation wireless communication such as the fifth generation mobile communication.
Example two
The difference between the method for selecting an antenna based on physical layer coding optimization for soft message forwarding in this embodiment and the first embodiment is that:
this embodiment is illustrated in detail by means of fig. 2-8.
The physical layer coding optimization antenna selection method based on selective soft message forwarding cooperation (SSMF) provided in this embodiment may be applied to a multi-relay wireless communication system, and implement effective and reliable transmission of information when the distance between communication nodes is long or there is an obstacle to block, and is not limited to the field described in detail in the following embodiments. And in the BC stage, the relay node deletes part of antennas from all the antennas to obtain an initial antenna set by taking the mutual information quantity of the two source nodes in the BC stage as a deletion standard without reducing the mutual information quantity of the two source nodes in the BC stage. Mutual information is a useful information metric in information theory, which is the unsuitability of a random variable to be reduced by the knowledge of another random variable. Then, the relay node takes the minimum mutual information quantity of the two source nodes in the time slot as a target function, selects an optimal antenna set from the initial antenna set, and averagely distributes the transmitting power to the antennas in the optimal antenna set.
Fig. 2 is a MIMO two-way relay network system model. By two user nodes S1And S2And a relay node R. The relay node R has M antennas, and M is a natural number greater than 0.
Fig. 3 is a comparison of end-to-end BER performance for different physical layer codes. In the former PNC based on SSMF cooperation, all antennas of the relay node participate in BC orderThe cooperative forwarding of the segments causes unreasonable energy consumption utilization of the relay nodes. Therefore, the present embodiment proposes an optimized antenna selection method based on the MMMI criterion. And the relay node deletes part of the antennas from all the antennas to obtain an initial antenna set by taking the mutual information quantity of the two source nodes at the stage as a deletion standard without reducing. Then, the relay node takes the minimum mutual information quantity of the two source nodes in the time slot as a target function, selects an optimal antenna set from the initial antenna set, and averagely distributes the transmitting power to the antennas in the optimal antenna set. In contrast to the original method, the antennas with better channel quality to the source node will be allocated more power, while those with poorer channel quality to the source node will not participate in the BC phase forwarding. As shown in FIG. 3, when the BER is 10-3In this embodiment, the optimized antenna selection method can obtain about 1dB performance gain.
Fig. 4 is a comparison of end-to-end throughput for different physical layer coding schemes. At low signal-to-noise ratio, the noise at each receiving antenna of the relay node is large. The BER in the BC stage remains a large value even if the relay node selects the smallest superposed signal for mapping. Therefore, when the signal-to-noise ratio is low, the SSMF cooperation of the optimized antenna selection method is not adopted, and the network throughput is slightly less than that of the cooperation of DF and SMF. However, when the optimized antenna selection method is adopted, the energy consumption of the system is reasonably utilized, and the BER performance is improved accordingly. Therefore, the network throughput of the SSMF cooperation adopting the optimized antenna selection method is greater than that of the cooperation of DF and SMF no matter the signal-to-noise ratio is low or high. And the throughput is close to the upper limit of 2.5Mbps at high signal-to-noise ratio.
FIG. 5 shows a source node S2And the distance from the relay node influences the transmitting power of each antenna of the relay node. With source node S2The distance between the relay node and the relay node is changed, and the distances between each antenna of the relay node and the two source nodes are always equal. Therefore, the channel quality from each antenna to the two source nodes is not greatly different. As shown in fig. 5, although the channel quality between each antenna and the two source nodes is different in a single forwarding process, the allocated energy is different from each other. However, in the process of multiple retransmission, the proportion of the total energy distributed to each antenna is not very different and is close to 1/6.
Fig. 6 shows a comparison of end-to-end BER performance before and after the optimization of the antenna selection method for different numbers of antennas. As shown in fig. 6, no matter whether the optimized antenna selection method is adopted or not, the BER performance of the system is improved to some extent as the number of antennas at the relay node increases. This is because as the number of antennas at the relay node increases, the system can obtain more diversity gain regardless of the MA or BC stage. As shown in FIG. 6, when the BER is 10-3When the relay node only has 2 antennae, the optimized antenna selection method is adopted to obtain about 3.5dB performance gain; but when the relay node has 8 antennas, the optimized antenna selection method can obtain about 9.5dB performance gain. This is because, in the BC stage, as the number of relay node antennas increases, the optimized antenna selection method can allocate more power to the antennas with higher channel quality between the relay nodes. Therefore, as the number of relay node antennas increases, the superiority of the optimized antenna selection method is more significant.
Fig. 7 is a comparison of end-to-end BER performance before and after antenna set pre-selection algorithm. The antenna set pre-selection method based on mutual information takes the mutual information quantity of two source nodes in the BC stage not to be reduced as a deletion standard. The method essentially eliminates antennas with channel quality lower than the average value from the set according to the equations (19) and (20). As shown in fig. 7, with different numbers of antennas, the BER performance of the system is not greatly affected by the antenna pre-selection method on the basis of reducing the complexity of the system.
Fig. 8 shows the average number of antennas in the initial antenna set after the antenna set pre-selection method is applied under different snr. Because the antenna set pre-selection method takes the average channel quality of all the antennas at the relay node as a deletion standard, the average number of the remaining antennas after the antenna set pre-selection method is adopted is basically kept unchanged along with the change of the signal-to-noise ratio.
In future 5G and next generation wireless communications, large-scale antenna transmission techniques are used by network base stations in each cell. Therefore, in the actual wireless communication process, a large number of MIMO bidirectional relay channels exist, and the method has high practical value.
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims (9)

1. A physical layer coding optimization antenna selection method based on soft message forwarding selection is characterized by comprising the following steps:
s1. user node SiSignal x to be transmittediTransmitting to a relay node R through a channel;
s2, the relay node R receives a signal xiObtaining a sum signal and a difference signal by adopting a sum-difference linear transformation method;
s3, the relay node R processes distortion introduced by a channel in the obtained sum signal and difference signal by adopting a zero forcing detection method to obtain a processed signal
Figure FDA0002361016950000016
S4, the relay node R screens the obtained processed signals
Figure FDA0002361016950000017
Mapping the screened signals into a log-likelihood form by adopting a log-likelihood ratio mapping method;
s5, deleting a part of antennas by the relay node R based on the mutual information antenna set pre-selection method to obtain an initial antenna set;
s6, the relay node R selects a required antenna set from the obtained initial antenna set based on an antenna selection method of a maximum and minimum mutual information criterion, and distributes transmitting power to the selected antenna set in the required antenna set averagely;
s7. the relay nodeThe point R sends the signal broadcast obtained by mapping to the user node S through the selected antenna in the required antenna seti；
S8, the user node SiAnd decoding the received signal by adopting a decoding mode based on threshold judgment to obtain a final result.
2. The method according to claim 1, wherein in step S1, the user node S is configured to optimize antenna selection based on selecting soft message forwarding physical layer codingiComprising S1And S2(ii) a The signal x to be transmittediIncluding x1And x2。
3. The method for selecting an antenna for optimized physical layer coding based on soft message forwarding according to claim 2, wherein in step S2, the relay node R receives the signal xiExpressed as:
Figure FDA0002361016950000011
Figure FDA0002361016950000012
wherein the content of the first and second substances,
Figure FDA0002361016950000013
respectively representing signals received by the 1 st and 2 nd sub antennas of the relay node R;
Figure FDA0002361016950000014
Figure FDA0002361016950000015
respectively representing user nodes S1、S2The transmit power of (a); h is11,1、h12,1、h21,1、h22,1Respectively representing user nodes S1、S2Channel coefficients of links between the 1 st and 2 nd antennas of the relay node R; n is1,1、n2,1Respectively representing additive white Gaussian noise at the 1 st pair of antennas and the 2 nd pair of antennas of the relay node R; x is the number of1、x2Respectively representing user nodes S1、S2The transmitted signal;
in step S2, the signal received by the relay node R
Figure FDA0002361016950000021
Expressed in matrix form as:
XR＝HX+N
Figure FDA0002361016950000022
wherein H, X, N represents a matrix or vector;
the step S2 further includes the relay node R performing sum-difference linear transformation on the received signal to obtain a sum signal and a difference signal, and detecting the obtained sum signal and difference signal, where the received signal of the relay node R is represented as:
Figure FDA0002361016950000023
Figure FDA0002361016950000024
Figure FDA0002361016950000025
wherein the content of the first and second substances,
Figure FDA0002361016950000026
a representation sum signal;
Figure FDA0002361016950000027
representing a difference signal.
4. The method as claimed in claim 3, wherein in step S3, the relay node R corrects the obtained sum and difference signals for channel-induced distortion by using a zero-forcing detection method, which is expressed as:
Figure FDA0002361016950000028
wherein the content of the first and second substances,
Figure FDA0002361016950000029
an equalization matrix representing a zero forcing detection method;
Figure FDA00023610169500000210
to represent
Figure FDA00023610169500000211
The conjugate transpose matrix of (a);
Figure FDA00023610169500000212
to represent
Figure FDA00023610169500000213
The inverse matrix of (d);
in step S3, a corrected signal is obtained
Figure FDA00023610169500000214
Expressed as:
Figure FDA00023610169500000215
Figure FDA00023610169500000216
wherein the content of the first and second substances,
Figure FDA00023610169500000217
represents the corrected signal;
Figure FDA00023610169500000218
respectively representing the noise at the 1 st and 2 nd sub-antennas amplified by the zero forcing detection method.
5. The method for selecting an antenna based on the physical layer coding optimization for soft message forwarding according to claim 4, wherein in step S4, the selected signals are mapped into log-likelihood form by using log-likelihood ratio mapping method, which is expressed as:
Figure FDA0002361016950000031
wherein the content of the first and second substances,
Figure FDA0002361016950000032
representing a signal variable x1、x2Exclusive or of;
Figure FDA0002361016950000033
represents the variance;
Figure FDA0002361016950000034
Figure FDA0002361016950000035
wherein the content of the first and second substances,
Figure FDA0002361016950000036
the formula is arranged as follows:
Figure FDA0002361016950000037
Figure FDA0002361016950000038
in step S4, the method further includes adding a 1-bit flag to the mapped data, which is expressed as:
Figure FDA0002361016950000041
where sign denotes a flag.
6. The method for selecting antennas based on physical layer coding optimization for soft message forwarding according to claim 5, wherein the step S5 comprises:
s51, the relay node R obtains the source node S from each antenna by adopting a channel estimation method1And S2The channel state information of (a);
s52, judging that the kth antenna of the relay node R reaches the source node S1And S2If the channel state information meets the deletion condition, the relay node R adds the kth antenna into the initial antenna set; wherein the deletion condition is expressed as:
Figure FDA0002361016950000042
Figure FDA0002361016950000043
wherein, N represents the number of antennas owned by the relay node R, and is a positive integer; h isij,2Indicating the relay node R ith antenna to the source node SjThe channel coefficients of the link between.
7. The method for selecting antennas based on physical layer coding optimization for soft message forwarding according to claim 6, wherein the step S6 comprises:
s61, when the relay node R calculates that all antennas in the initial antenna set participate in forwarding, the source node S1And S2The obtained mutual information quantity;
s62, calculating a source node S by a relay node R1And S2Initial minimum mutual information amount;
s63, the relay node R selects antennas from the initial antenna set one by one to delete the antennas, a new antenna set is obtained, and a source node S of the new antenna set is calculated1And S2Minimum mutual information amount of (a);
s64, judging whether the minimum mutual information quantity of the new antenna set is larger than or equal to the initial antenna set, if so, taking the new antenna set and the minimum mutual information quantity as the initial antenna set and the initial mutual information quantity, and executing the step S63; if not, the execution is finished.
8. The method for selecting antennas based on physical layer coding optimization for soft message forwarding according to claim 7, wherein the mutual information obtained in step S61 is represented as:
Figure FDA0002361016950000051
Figure FDA0002361016950000052
wherein the content of the first and second substances,
Figure FDA0002361016950000053
and
Figure FDA0002361016950000054
respectively representing source nodes S1And S2In the antenna set RiMutual information amount obtained under the condition;
Figure FDA0002361016950000055
representing the transmitting power of the jth antenna of the relay node R; h isij,2Indicating the relay node R ith antenna to the source node SjChannel coefficients of the inter-link; n' represents the number of antennas in the initial antenna set;
Figure FDA0002361016950000056
representing a source node SiVariance of white gaussian noise; when the antennas in the initial antenna set are all participating in the retransmission,
Figure FDA0002361016950000057
wherein, PrRepresenting the total transmit power of the relay node R.
9. The method of claim 8, wherein the source node S is calculated in step S621And S2The initial minimum mutual information amount is expressed as:
Figure FDA0002361016950000058
wherein, Imin,iRepresenting a source node S1And S2In the antenna set RiMinimum mutual information amount obtained under the condition;
the step S63 is specifically to delete the antenna a from the initial antenna set1Obtaining a new antenna set
Figure FDA0002361016950000059
Wherein
Figure FDA00023610169500000510
Indicating the deletion of antenna a from the original set of antennasiObtaining a new antenna set; new antenna source node S1And S2The minimum mutual information amount can be expressed as:
Figure FDA00023610169500000511
wherein the content of the first and second substances,
Figure FDA00023610169500000512
Figure FDA00023610169500000513
Figure FDA00023610169500000514
repeatedly executing to obtain the minimum mutual information quantity of the new antenna set to obtain N' minimum mutual information quantities;
selecting the largest minimum mutual information quantity from the N' minimum mutual information quantities as the minimum mutual information quantity after deleting 1 antenna, wherein the minimum mutual information quantity is expressed as follows:
Figure FDA00023610169500000515
in step S64, it is determined whether the minimum mutual information amount of the new antenna set is greater than or equal to the initial antenna set, and the determination is represented as:
Imin,1/Imin,0≥1。
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