CN112217606B - Interference elimination method and device for colored noise, electronic equipment and storage medium - Google Patents

Interference elimination method and device for colored noise, electronic equipment and storage medium Download PDF

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CN112217606B
CN112217606B CN202010942343.5A CN202010942343A CN112217606B CN 112217606 B CN112217606 B CN 112217606B CN 202010942343 A CN202010942343 A CN 202010942343A CN 112217606 B CN112217606 B CN 112217606B
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牛凯
贺志强
龙非
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Beijing University of Posts and Telecommunications
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00—Arrangements for detecting or preventing errors in the information received
    • H04L1/004—Arrangements for detecting or preventing errors in the information received by using forward error control
    • H04L1/0045—Arrangements at the receiver end
    • H04L1/0054—Maximum-likelihood or sequential decoding, e.g. Viterbi, Fano, ZJ algorithms
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
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    • 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
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Abstract

One or more embodiments of the present specification provide a method, an apparatus, an electronic device, and a storage medium for interference cancellation of colored noise; the method comprises the following steps: initializing interference elimination related parameters by utilizing a colored noise covariance matrix; carrying out interference elimination on the received signal by using a GAMP algorithm to obtain an external log-likelihood ratio of the coded bits; BCJR decoding is used for the external log-likelihood ratio of the coded bits to obtain the prior log-likelihood ratio of the coded bits; calculating the prior probability of the constellation symbol; and (3) the prior probability of the constellation symbols is substituted back into GAMP interference elimination, iterative circulation is carried out, and after the set maximum iteration times are reached, judgment information bits are output to complete the interference elimination. The method improves the bit error performance of linear modulation, enhances the effectiveness and the reliability of a communication system, and greatly reduces the complexity of interference elimination.

Description

Interference elimination method and device for colored noise, electronic equipment and storage medium
Technical Field
One or more embodiments of the present disclosure relate to the field of communications technologies, and in particular, to a method and an apparatus for interference cancellation of colored noise, an electronic device, and a storage medium.
Background
The broadband linear modulation system mainly faces three types of interference, (1) intersymbol interference caused by shaping pulse; (2) intersymbol interference caused by channel multipath; (3) colored noise, for example, marine noise in an underwater acoustic communication scenario. For linear modulation systems, the first two have resulted in better solutions, while colored noise is usually approximated as white gaussian noise.
In the prior art, on one hand, colored noise is approximated to white gaussian noise, and elements outside a diagonal line of a covariance matrix of the colored noise are usually ignored, which can seriously affect the bit error performance of a receiver; on the other hand, matrix inversion operation is often required for interference cancellation, and when the number of transmitted symbols is large or the oversampling multiple is large, the complexity is extremely high, and the realization is difficult.
Disclosure of Invention
In view of the above, an object of one or more embodiments of the present disclosure is to provide a method, an apparatus, an electronic device, and a storage medium for interference cancellation of colored noise, so as to solve the problems of too high bit error rate and too high complexity of interference cancellation of a receiver.
In view of the above, one or more embodiments of the present specification provide a method for interference cancellation of colored noise, including:
initializing interference elimination related parameters by utilizing a colored noise covariance matrix;
according to the interference elimination related parameters, carrying out interference elimination on the received signals by using a GAMP algorithm to obtain an external log-likelihood ratio of the coded bits;
BCJR decoding is used for the external log-likelihood ratio of the coded bits to obtain the prior log-likelihood ratio of the coded bits;
calculating the prior probability of the constellation symbol according to the prior log-likelihood ratio of the coded bit;
and substituting the prior probability of the constellation symbols back into the step of carrying out interference elimination on the received signals by using the GAMP algorithm, carrying out iterative circulation, and outputting judgment information bits after the set maximum iteration times are reached to finish the interference elimination.
Based on the same inventive concept, one or more embodiments of the present specification further provide an interference cancellation apparatus for colored noise, including:
a parameter initialization module configured to initialize interference cancellation related parameters using the colored noise covariance matrix;
a GAMP interference elimination module configured to perform interference elimination on the received signal by using a GAMP algorithm according to the interference elimination related parameters to obtain an external log likelihood ratio of the coded bits;
a BCJR decoding module configured to decode the external log-likelihood ratio of the coded bits by using BCJR to obtain a priori log-likelihood ratio of the coded bits;
an iterative loop module configured to compute prior probabilities of constellation symbols from prior log-likelihood ratios of the coded bits; and substituting the prior probability of the constellation symbols back into the GAMP interference elimination module to carry out iterative circulation, and outputting judgment information bits after the set maximum iteration times are reached to finish interference elimination.
Based on the same inventive concept, one or more embodiments of the present specification further provide an electronic device, which includes a memory, a processor, and a computer program stored on the memory and executable on the processor, and the processor implements the method as described in any one of the above items when executing the program.
Based on the same inventive concept, one or more embodiments of the present specification also provide a non-transitory computer-readable storage medium storing computer instructions for causing the computer to perform the method as any one of the above.
As can be seen from the foregoing, in the method, the apparatus, the electronic device, and the storage medium for eliminating interference of colored noise provided in one or more embodiments of the present disclosure, on the basis of the prior art, a covariance matrix of the colored noise is fully considered, so that a bit error performance of linear modulation is improved, and effectiveness and reliability of a communication system are enhanced; by utilizing the characteristic that GAMP does not need matrix inversion, the complexity of interference elimination is greatly reduced.
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In order to more clearly illustrate one or more embodiments or prior art solutions of the present specification, the drawings that are needed in the description of the embodiments or prior art will be briefly described below, and it is obvious that the drawings in the following description are only one or more embodiments of the present specification, and that other drawings may be obtained by those skilled in the art without inventive effort from these drawings.
Fig. 1 is a flow diagram of a method for interference cancellation of colored noise according to one or more embodiments of the present disclosure;
fig. 2 is a schematic diagram of a receiving end structure according to one or more embodiments of the present disclosure;
fig. 3 is a schematic diagram of a factor graph structure of receiving-end GAMP interference cancellation according to one or more embodiments of the present disclosure;
FIG. 4 is a graph comparing bit error rate performance with a prior art interference cancellation method for colored noise in one or more embodiments of the present disclosure;
FIG. 5 is a three-dimensional graphical representation of a covariance matrix of colored noise in one or more embodiments of the disclosure;
fig. 6 is a schematic structural diagram of an interference cancellation apparatus for colored noise according to one or more embodiments of the present disclosure;
fig. 7 is a schematic structural diagram of an electronic device according to one or more embodiments of the present disclosure.
Detailed Description
For the purpose of promoting a better understanding of the objects, aspects and advantages of the present disclosure, reference is made to the following detailed description taken in conjunction with the accompanying drawings.
It is to be noted that unless otherwise defined, technical or scientific terms used in one or more embodiments of the present specification should have the ordinary meaning as understood by those of ordinary skill in the art to which this disclosure belongs. The use of "first," "second," and similar terms in one or more embodiments of the specification is not intended to indicate any order, quantity, or importance, but rather is used to distinguish one element from another. The word "comprising" or "comprises", and the like, means that the element or item listed before the word covers the element or item listed after the word and its equivalents, but does not exclude other elements or items. The terms "connected" or "coupled" and the like are not restricted to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "upper", "lower", "left", "right", and the like are used merely to indicate relative positional relationships, and when the absolute position of the object being described is changed, the relative positional relationships may also be changed accordingly.
As described in the background section, in the existing interference cancellation method for colored noise, on one hand, the colored noise is approximated to gaussian white noise, and elements outside a diagonal of a covariance matrix of the colored noise are usually ignored, which may have a serious influence on the bit error performance of a receiver; on the other hand, matrix inversion operation is often required for interference cancellation, and when the number of transmitted symbols is large or the oversampling multiple is large, the complexity is extremely high, and the realization is difficult.
Aiming at the problems in the prior art, the invention fully considers the covariance matrix of colored noise on the basis of the prior art, improves the bit error performance of linear modulation, and enhances the effectiveness and reliability of a communication system; and the complexity of interference elimination is greatly reduced by utilizing the characteristic that GAMP does not need matrix inversion.
The technical solutions of one or more embodiments of the present specification are described in detail below with reference to specific embodiments.
One or more embodiments of the present specification provide a method of interference cancellation of colored noise. Referring to fig. 2, the iterative interference cancellation method based on Generalized Approximate Message Passing (GAMP) for linear modulation according to the present invention obtains Cholesky decomposition of a covariance matrix of colored noise through a second-order statistical characteristic of the colored noise, and converts the colored noise into white noise; further, according to the factor graph structure of the received signal, the sending constellation symbol and the white noise, GAMP is used for eliminating interference on the received signal, and intersymbol interference is eliminated; and iterate with the BCJR decoder of the convolutional code, reduce the bit error rate; and finally, outputting decision information bits to finish interference elimination.
In this embodiment, referring to fig. 3, the relationship between the received signal 301 and the transmitted constellation symbol 302 and the white noise 303 after whitening transformation can be represented by a factor graph. According to the factor graph structure, the invention utilizes GAMP to eliminate the interference of the received signal and repeatedly eliminates the interference in an iterative mode.
The method is suitable for a linear modulation system, a vector formed by sending constellation symbols in the system is beta, and the size of the vector is Nx 1, wherein N is the size of the vector obtained after vector beta is precoded. The baseband receiving signal at the receiving end is:
y≈HAPβ+n
wherein H is a number OsN×OsN of a matrix of a combination of multipath channels and a low pass filter, A being of size OsUp-sampling matrix of NxN, OsIs an oversampling multiple, P is a precoding matrix of size N × M, the vector N represents the colored noise, which follows a complex gaussian distribution with a mean value of
Figure BDA0002674056800000041
The covariance matrix is Σ, both known at the receiving end,
Figure BDA0002674056800000042
is of size OsA vector of all zeros of x 1.
Referring to fig. 1, the method for eliminating colored noise interference according to the present invention includes the following steps:
and step S1, initializing interference elimination related parameters by using the colored noise covariance matrix.
In this embodiment, first, the composite matrix G is calculated as HAP, Cholesky decomposition is performed on the covariance matrix Σ of the colored noise to obtain a lower triangular matrix Δ, and the requirement of Σ as Δ is satisfiedHTherein,. 1-HRepresenting the conjugate transpose of the matrix.
With Cholesky decomposition, the colored noise n can be represented as n ═ Δ w, where the vector w ═ Δ w-1n is the white Gaussian noise obtained after the colored noise whitening transformation, and the white Gaussian noise obeys the complex Gaussian distribution with the mean value of
Figure BDA0002674056800000051
The covariance matrix is
Figure BDA0002674056800000052
Wherein the content of the first and second substances,
Figure BDA0002674056800000053
denotes the size OsAnd N unit square matrix.
Setting the initialization iteration number I to be 0, and setting the maximum iteration number ImaxSetting the maximum number of GAMP iterations Tmax(ii) a Transmitting an mth constellation symbol beta of a symbol vector betamIs a priori distributed as paβm＝χ q1/Q, M-0, M-1, Q, wherein Q is the modulation order, χqIs the qth constellation point in the constellation set.
Step S2, according to the interference elimination related parameters, using GAMP algorithm to eliminate the interference of the received signal, and obtaining the external log likelihood ratio of the coded bit;
the method specifically comprises the following nine sub-steps:
step S201, initializing a vector formed by a first derivative
Figure BDA0002674056800000054
Wherein [ ·]Values within indicate the number of iterations of GAMP; initializing an outer mean of a symbol vector beta
Figure BDA0002674056800000055
Vector μ formed by external variancese,β[0]＝∞1M×1Wherein 1 isM×1Representing a full 1 matrix of size M x 1, with ∞ representing a sufficiently large number, e.g. 104(ii) a According to probability distribution
Figure BDA0002674056800000056
Calculating the posterior mean of the transmitted symbol vector
Figure BDA0002674056800000057
Sum variance
Figure BDA0002674056800000058
Wherein the content of the first and second substances,
Figure BDA0002674056800000059
and
Figure BDA00026740568000000510
respectively represent
Figure BDA00026740568000000511
And mue,β[0]The mth element of (1); posterior mean of initialization white noise w
Figure BDA00026740568000000512
Vectors formed by external variances
Figure BDA00026740568000000513
The number of initialization GAMP iterations t is 0.
Step S202, calculating prior mean vector of linear modulation sending signal
Figure BDA00026740568000000514
And a prior variance vector mup[t]：
Figure BDA0002674056800000061
Wherein |. non chlorine2The square modulo the element of the matrix in brackets is shown,
Figure BDA0002674056800000062
representing element-by-element multiplication between matrices, vectors
Figure BDA0002674056800000063
(Vector)
Figure BDA0002674056800000064
Step S203, calculating a vector formed by a first derivative and a second derivative
Figure BDA0002674056800000065
And mus[t]：
Figure BDA0002674056800000066
Where,/denotes the element-by-element division between the matrices.
Step S204, calculating an external mean value of the constellation symbol vector beta
Figure BDA0002674056800000067
Sum variance μe,β[t]：
Figure BDA0002674056800000068
Step S205, according to the probability distribution
Figure BDA0002674056800000069
Figure BDA00026740568000000610
Calculating the posterior mean of the transmitted symbol vector
Figure BDA00026740568000000611
Sum variance μβ[t]。
Step S206, calculating the external mean value of the white noise vector w
Figure BDA00026740568000000612
Sum variance μe,w[t]：
Figure BDA00026740568000000613
Step S207, calculating posterior mean value of white noise vector w
Figure BDA00026740568000000614
Sum variance μd,w[t]：
Figure BDA00026740568000000615
Step S208, recalculating the number of GAMP iterations t to t +1
Figure BDA0002674056800000071
μp[t]、
Figure BDA0002674056800000072
μs[t]、
Figure BDA0002674056800000073
μe,β[t]、
Figure BDA0002674056800000074
μβ[t]、
Figure BDA0002674056800000075
μe,w[t]、
Figure BDA0002674056800000076
μd,w[t]。
Step S209, when GAMP is overlappedThe generation number reaches a set threshold value T ═ TmaxLet constellation symbol betamCorresponding ith code bit is cm,i∈0,1，i＝1,...,log2Q, external log-likelihood ratio lambda of the output coded bitsEcmi,：
Figure BDA0002674056800000077
Wherein, the set q is cm,iB denotes a coded bit vector
Figure BDA0002674056800000078
A set formed by the serial numbers of the constellation points after the constellation mapping operation.
Step S3, BCJR decoding is used for the external log-likelihood ratio of the coded bits to obtain the prior log-likelihood ratio lambda of the coded bitsA
Figure BDA0002674056800000079
And step S4, calculating the prior probability of the constellation symbol according to the prior log-likelihood ratio of the coded bit.
In the present embodiment, the a priori log likelihood ratio λ is determined based on the coded bitsA
Figure BDA00026740568000000710
Calculating a constellation symbol betamM0, a priori probability p of M1aβm：
Figure BDA00026740568000000711
Wherein, aggregate
Figure BDA00026740568000000712
And the sequence number q of the constellation point is represented by a set formed by coded bits after constellation inverse mapping operation mapping.
And step S5, substituting the prior probability of the constellation symbol back into the step of using the GAMP algorithm to eliminate the interference of the received signal, performing iterative loop, and outputting a judgment information bit after the set maximum iteration times is reached to complete the interference elimination.
In this embodiment, let the number of iterations I equal to I +1, and calculate λ againA
Figure BDA00026740568000000713
paβmAnd the result is substituted back into step S2, and interference cancellation is performed again using the GAMP algorithm.
Until the number of iterations reaches a threshold value I ═ ImaxAnd outputting the judgment information bit, terminating the iterative processing and ending the whole process.
As an alternative embodiment, referring to fig. 4, it is a graph comparing the embodiment of the interference cancellation method for colored noise of the present invention with the prior art regarding bit error rate performance. The embodiment uses a single carrier modulation mode, the constellation set is QPSK, and the precoding matrix P is IMThe filter has no multipath fading, the low-pass filter is a root raised cosine roll-off filter (sRC), the roll-off coefficient is 0.5, and the oversampling multiple is OsThe transmit symbol vector size M-N-64. This embodiment employs a random interleaver and a systematic convolutional code with code rate 1/2, which generates a polynomial of [1+ D2,1+D+D2]The number of iterations is set to Tmax＝Imax＝2。
As can be seen from fig. 4, compared with the prior art, the present embodiment has a signal-to-noise ratio (SNR) gain of about 1.5dB when the Bit Error Rate (BER) is 10^ -4, because the method of the present invention fully utilizes the covariance matrix of the colored noise, and improves the bit error performance of the receiver by using the space between the GAMP interference cancellation and the channel soft decoding.
As an alternative embodiment, referring to fig. 5, a covariance matrix of colored noise used in the embodiment of the present invention is shown.
As can be seen from the above embodiments, the interference cancellation method for colored noise of the present embodiment fully considers the covariance matrix of the colored noise on the basis of the prior art, improves the bit error performance of linear modulation, and enhances the effectiveness and reliability of the communication system; by utilizing the characteristic that GAMP does not need matrix inversion, the complexity of interference elimination is greatly reduced.
It should be noted that the interference cancellation method for colored noise according to one or more embodiments of the present disclosure may be performed by a single device, such as a computer or a server. The method of the embodiment can also be applied to a distributed scene and completed by the mutual cooperation of a plurality of devices. In such a distributed scenario, one of the devices may perform only one or more steps of the method of one or more embodiments of the present disclosure, and the devices may interact with each other to complete the method.
The foregoing description has been directed to specific embodiments of this disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
Based on the same inventive concept, one or more embodiments of the present specification further provide an interference cancellation apparatus for colored noise. Referring to fig. 6, the interference cancellation apparatus for colored noise includes:
a parameter initialization module 601 configured to initialize interference cancellation related parameters by using the colored noise covariance matrix;
a GAMP interference cancellation module 602 configured to perform interference cancellation on the received signal using GAMP algorithm according to the interference cancellation related parameter, to obtain an external log likelihood ratio of the coded bits;
a BCJR decoding module 603 configured to decode the external log-likelihood ratios of the coded bits by using BCJR to obtain prior log-likelihood ratios of the coded bits;
an iterative loop module 604 configured to compute prior probabilities of constellation symbols from the prior log-likelihood ratios of the coded bits; and substituting the prior probability of the constellation symbols back into the GAMP interference elimination module to carry out iterative circulation, and outputting judgment information bits after the set maximum iteration times are reached to finish interference elimination.
For convenience of description, the above devices are described as being divided into various modules by functions, and are described separately. Of course, the functionality of the modules may be implemented in the same one or more software and/or hardware implementations in implementing one or more embodiments of the present description.
The interference cancellation apparatus in the foregoing embodiment is used to implement the interference cancellation method for colored noise in the foregoing embodiment, and has the beneficial effects of the interference cancellation method embodiment for colored noise, which are not described herein again.
Based on the same inventive concept, one or more embodiments of the present specification further provide an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, the processor implements the interference cancellation method for colored noise according to any one of the above embodiments.
Fig. 7 is a schematic diagram illustrating a more specific hardware structure of an electronic device according to this embodiment, where the electronic device may include: a processor 1010, a memory 1020, an input/output interface 1030, a communication interface 1040, and a bus 1050. Wherein the processor 1010, memory 1020, input/output interface 1030, and communication interface 1040 are communicatively coupled to each other within the device via bus 1050.
The processor 1010 may be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an Application Specific Integrated Circuit (ASIC), or one or more Integrated circuits, and is configured to execute related programs to implement the technical solutions provided in the embodiments of the present disclosure.
The Memory 1020 may be implemented in the form of a ROM (Read Only Memory), a RAM (Random Access Memory), a static storage device, a dynamic storage device, or the like. The memory 1020 may store an operating system and other application programs, and when the technical solution provided by the embodiments of the present specification is implemented by software or firmware, the relevant program codes are stored in the memory 1020 and called to be executed by the processor 1010.
The input/output interface 1030 is used for connecting an input/output module to input and output information. The i/o module may be configured as a component in a device (not shown) or may be external to the device to provide a corresponding function. The input devices may include a keyboard, a mouse, a touch screen, a microphone, various sensors, etc., and the output devices may include a display, a speaker, a vibrator, an indicator light, etc.
The communication interface 1040 is used for connecting a communication module (not shown in the drawings) to implement communication interaction between the present apparatus and other apparatuses. The communication module can realize communication in a wired mode (such as USB, network cable and the like) and also can realize communication in a wireless mode (such as mobile network, WIFI, Bluetooth and the like).
Bus 1050 includes a path that transfers information between various components of the device, such as processor 1010, memory 1020, input/output interface 1030, and communication interface 1040.
It should be noted that although the above-mentioned device only shows the processor 1010, the memory 1020, the input/output interface 1030, the communication interface 1040 and the bus 1050, in a specific implementation, the device may also include other components necessary for normal operation. In addition, those skilled in the art will appreciate that the above-described apparatus may also include only those components necessary to implement the embodiments of the present description, and not necessarily all of the components shown in the figures.
Based on the same inventive concept, one or more embodiments of the present specification also provide a non-transitory computer-readable storage medium storing computer instructions for causing the computer to perform the interference cancellation method of colored noise according to any one of the above embodiments.
Computer-readable media of the present embodiments, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device.
Those of ordinary skill in the art will understand that: the discussion of any embodiment above is meant to be exemplary only, and is not intended to intimate that the scope of the disclosure, including the claims, is limited to these examples; within the spirit of the present disclosure, features from the above embodiments or from different embodiments may also be combined, steps may be implemented in any order, and there are many other variations of different aspects of one or more embodiments of the present description as described above, which are not provided in detail for the sake of brevity.
While the present disclosure has been described in conjunction with specific embodiments thereof, many alternatives, modifications, and variations of these embodiments will be apparent to those of ordinary skill in the art in light of the foregoing description. For example, other memory architectures (e.g., dynamic ram (dram)) may use the discussed embodiments.
It is intended that the one or more embodiments of the present specification embrace all such alternatives, modifications and variations as fall within the broad scope of the appended claims. Therefore, any omissions, modifications, substitutions, improvements, and the like that may be made without departing from the spirit and principles of one or more embodiments of the present disclosure are intended to be included within the scope of the present disclosure.

Claims (9)

1. A method for interference cancellation of colored noise, comprising:
initializing interference elimination related parameters by utilizing a colored noise covariance matrix;
the first stageThe method comprises the steps of calculating a composite matrix G (HAP), performing Cholesky decomposition on a covariance matrix sigma of colored noise to obtain a lower triangular matrix delta, and satisfying the condition that sigma is deltaHWherein, wherein-HRepresents a conjugate transpose of the matrix; with Cholesky decomposition, the colored noise n can be represented as n ═ Δ w, where the vector w ═ Δ w-1n is the white Gaussian noise obtained after the colored noise whitening transformation, and the white Gaussian noise obeys the complex Gaussian distribution with the mean value of
Figure FDA0003218992680000011
The covariance matrix is
Figure FDA0003218992680000012
Wherein the content of the first and second substances,
Figure FDA0003218992680000013
denotes the size OsA unit square matrix of N;
setting the initialization iteration number I to be 0, and setting the maximum iteration number ImaxSetting the maximum number of GAMP iterations Tmax(ii) a Transmitting an mth constellation symbol beta of a symbol vector betamIs a priori distributed as pa(βm＝χq) 1/Q, M-0, M-1, Q, wherein Q is the modulation order, χqIs the qth constellation point in the constellation set;
according to the interference elimination related parameters, carrying out interference elimination on the received signals by using a GAMP algorithm to obtain an external log-likelihood ratio of the coded bits;
BCJR decoding is used for the external log-likelihood ratio of the coded bits to obtain the prior log-likelihood ratio of the coded bits;
calculating the prior probability of the constellation symbol according to the prior log-likelihood ratio of the coded bit;
and substituting the prior probability of the constellation symbols back into the step of carrying out interference elimination on the received signals by using the GAMP algorithm, carrying out iterative circulation, and outputting judgment information bits after the set maximum iteration times are reached to finish the interference elimination.
2. The method according to claim 1, wherein the interference cancellation method is applied to a linear modulation system, and a vector formed by the transmitted constellation symbols in the system is β, and the size is N × 1, where N is the size of the vector obtained by precoding the vector β; the baseband receiving signal at the receiving end is: y ≈ HAP β + n where H is of size OsN×OsN of a matrix of a combination of multipath channels and a low pass filter, A being of size OsUp-sampling matrix of NxN, OsIs an oversampling multiple, P is a precoding matrix of size N × M, the vector N represents the colored noise, which follows a complex gaussian distribution with a mean value of
Figure FDA0003218992680000021
The covariance matrix is Σ, both known at the receiving end,
Figure FDA0003218992680000022
is of size OsA vector of all zeros of x 1.
3. The colored noise interference cancellation method according to claim 1, wherein the GAMP interference cancellation algorithm specifically comprises:
initializing vectors formed by first derivatives
Figure FDA0003218992680000023
Wherein [ ·]Values within indicate the number of iterations of GAMP; initializing an outer mean of a symbol vector beta
Figure FDA0003218992680000024
Vector μ formed by external variancese,β[0]＝∞1M×1Wherein 1 isM×1Represents a full 1 matrix of size mx 1, and ∞ represents an infinite number; according to probability distribution
Figure FDA0003218992680000025
Q1.., Q, meterCalculating the posterior mean of a transmitted symbol vector
Figure FDA0003218992680000026
Sum variance
Figure FDA0003218992680000027
M-0., M-1, wherein,
Figure FDA0003218992680000028
and
Figure FDA0003218992680000029
respectively represent
Figure FDA00032189926800000210
And mue,β[0]The mth element of (1); posterior mean of initialization white noise w
Figure FDA00032189926800000211
Vectors formed by external variances
Figure FDA00032189926800000212
Initializing GAMP iteration times t to be 0;
calculating a prior mean vector of a linear modulated transmit signal
Figure FDA00032189926800000213
And a prior variance vector mup[t]：
Figure FDA00032189926800000214
Wherein |. non chlorine2The square modulo the element of the matrix in brackets is shown,
Figure FDA00032189926800000219
representing element-by-element multiplication between matrices, vectors
Figure FDA00032189926800000215
(Vector)
Figure FDA00032189926800000216
Calculating vectors of first and second derivatives
Figure FDA00032189926800000217
And mus[t]：
Figure FDA00032189926800000218
Where,/represents the element-by-element division between matrices;
computing an external mean of a constellation symbol vector beta
Figure FDA0003218992680000031
Sum variance μe,β[t]：
Figure FDA0003218992680000032
According to probability distribution
Figure FDA0003218992680000033
Q-1, Q, M-0, M-1, calculating a posterior mean of the transmit symbol vectors
Figure FDA0003218992680000034
Sum variance μβ[t]；
Computing an external mean of a white noise vector w
Figure FDA0003218992680000035
Sum variance μe,w[t]：
Figure FDA0003218992680000036
Calculating posterior mean of white noise vector w
Figure FDA0003218992680000037
Sum variance μd,w[t]：
Figure FDA0003218992680000038
4. The method of interference cancellation for colored noise according to claim 3, wherein said GAMP iteration specifically comprises:
let GAMP iteration number t be t +1, calculate again
Figure FDA0003218992680000039
μp[t]、
Figure FDA00032189926800000310
μs[t]、
Figure FDA00032189926800000311
μe,β[t]、
Figure FDA00032189926800000312
μβ[t]、
Figure FDA00032189926800000313
μe,w[t]、
Figure FDA00032189926800000314
μd,w[t]；
When the GAMP iteration number reaches a set threshold value T ═ TmaxLet constellation symbol betamCorresponding ith code bit is cm,i∈{0,1}，i＝1,...,log2Q, external log-likelihood ratio of output coded bits
Figure FDA00032189926800000315
Wherein, the set { q: cm,iB represents a coded bit vector
Figure FDA00032189926800000316
A set formed by the serial numbers of the constellation points after the constellation mapping operation.
5. The method of interference cancellation for colored noise according to claim 1, wherein said calculating the prior probability of the constellation symbol is based on a prior log likelihood ratio λ of the coded bitsA(cm,q) Calculating with respect to the constellation symbol betamM-0, a priori probability p of M-1a(βm)：
Figure FDA0003218992680000041
Wherein, aggregate
Figure FDA0003218992680000042
And the sequence number q of the constellation point is represented by a set formed by coded bits after constellation inverse mapping operation mapping.
6. The method of claim 1, wherein the step of substituting the prior probabilities of the constellation symbols back into the GAMP algorithm for interference cancellation of the received signal comprises calculating λ again by using I +1 as the iteration numberA(cm,q)、pa(βm) And interference cancellation is performed again using the GAMP algorithm.
7. An apparatus for removing colored noise interference, comprising:
a parameter initialization module configured to initialize interference cancellation related parameters using the colored noise covariance matrix; the initialization interference cancellation related parameter is to calculate a composite matrix G ═ HAP, perform Cholesky decomposition on a covariance matrix sigma of colored noise to obtain a lower triangular matrix delta, and satisfy the condition that ∑ ΔHWherein, wherein-HRepresents a conjugate transpose of the matrix; with Cholesky decomposition, the colored noise n can be represented as n ═ Δ w, where the vector w ═ Δ w-1n is white Gaussian noise obtained after the colored noise is whitened and transformed, and the white Gaussian noise obeys complex Gaussian distributionMean value of
Figure FDA0003218992680000043
The covariance matrix is
Figure FDA0003218992680000044
Wherein the content of the first and second substances,
Figure FDA0003218992680000045
denotes the size OsA unit square matrix of N;
setting the initialization iteration number I to be 0, and setting the maximum iteration number ImaxSetting the maximum number of GAMP iterations Tmax(ii) a Transmitting an mth constellation symbol beta of a symbol vector betamIs a priori distributed as pa(βm＝χq) 1/Q, M-0, M-1, Q, wherein Q is the modulation order, χqIs the qth constellation point in the constellation set;
a GAMP interference elimination module configured to perform interference elimination on the received signal by using a GAMP algorithm according to the interference elimination related parameters to obtain an external log likelihood ratio of the coded bits;
a BCJR decoding module configured to decode the external log-likelihood ratio of the coded bits by using BCJR to obtain a priori log-likelihood ratio of the coded bits;
an iterative loop module configured to compute prior probabilities of constellation symbols from prior log-likelihood ratios of the coded bits; and substituting the prior probability of the constellation symbols back into the GAMP interference elimination module to carry out iterative circulation, and outputting judgment information bits after the set maximum iteration times are reached to finish interference elimination.
8. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the method according to any of claims 1 to 6 when executing the program.
9. A non-transitory computer readable storage medium storing computer instructions for causing a computer to perform the method of any one of claims 1 to 6.
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