CN113765554B - SCMA codebook design method based on moth fire-fighting algorithm - Google Patents

SCMA codebook design method based on moth fire-fighting algorithm Download PDF

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CN113765554B
CN113765554B CN202111095292.8A CN202111095292A CN113765554B CN 113765554 B CN113765554 B CN 113765554B CN 202111095292 A CN202111095292 A CN 202111095292A CN 113765554 B CN113765554 B CN 113765554B
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何超
何春
朱立东
王剑
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University of Electronic Science and Technology of China
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    • 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
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Abstract

The invention provides a method for designing an SCMA codebook based on a moth fire suppression algorithm, which comprises the steps of determining optimized parameters according to the parameters in the SCMA codebook and user code words; and then constructing an SCMA codebook to be optimized, and finally obtaining the optimal parameter value of the parameter to be optimized by using the moth fire suppression algorithm with the SCMA codebook to be optimized as a criterion, thereby obtaining the optimal SCMA codebook according to the optimal parameter value. The method can be suitable for SCMA codebook design under different channels, and only SCMA channel parameters in the bit error rate function f _ BER are replaced under different channels; along with the increase of the number of users, the complexity of the moth fire suppression algorithm is slowly increased, and the realization is simple; according to the simulation result, the bit error rate of the codebook obtained by the method is obviously improved compared with other codebooks under the Gaussian channel and the Rayleigh channel.

Description

SCMA codebook design method based on moth fire-fighting algorithm
Technical Field
The invention relates to a wireless communication technology, in particular to a moth fire suppression algorithm-based non-orthogonal multiple access system codebook technology.
Background
In recent years, with the development of society, communication technology has advanced, and a mobile communication system has become one of the most critical information networks of human society. The Fifth Generation mobile communication system 5G (Fifth-Generation) has high requirements in terms of higher spectral efficiency, large-scale connection, lower delay, etc., and the conventional orthogonal Multiple access OMA (orthogonal Multiple access) technology cannot meet the requirement of 5G because the number of resource blocks and the number of users must be consistent due to orthogonality. A Non-Orthogonal Multiple Access (NOMA) technology is a technology for meeting the requirement of 5G, and can support an overload system with the number of users much larger than the number of resource blocks, and in the NOMA in the power domain, different levels of power are distributed to different users; in NOMA of the code domain, different users use different code words or signatures. The low Density signature lds (low Density signature) technique is a code domain NOMA technique, where user bits are multiplied by different sparse spreading signatures, which are mapped to modulation constellation points for transmission.
Nikoporu et al propose sparse Code division Multiple Access (SCMA) (sparse Code Multiple Access) technology for improving LDS technology, the SCMA is essentially the combination of spread spectrum and modulation mapping, based on a special factor graph, user Code words are directly mapped into sparse multidimensional Code words, and the SCMA can obtain larger shaping gain than LDS. Nikopor and H.Baligh, "spark code multiplex access,"2013 IEEE 24th Annual International Symposium on Personal, Indor, and Mobile Radio Communications (PIMRC),2013, pp.332-336, doi: 10.1109/PIMRC.2013.66156.
The SCMA codebook design is a more complex multidimensional problem, Taherzadeh, Nikopour and the like firstly propose an SCMA design method which is based on the design of a grid constellation and is divided into three steps, wherein the first step is the design of a factor graph, and the factor graph determines the number of users overlapping on a resource block and the number of non-zero elements; constructing a multidimensional mother constellation, specifically constructing a multidimensional constellation which maximizes the minimum Euclidean distance, and then rotating the constellation to obtain the multidimensional constellation with the Euclidean distance unchanged and the product distance of the constellation points increased; the third step is the operations of phase rotation, code word rearrangement, etc. of the mother constellation to obtain the difference between the users. The design of SCMA codebooks based on distance spectra is based on this approach. M.Taherzadeh, H.Nikopour, A.Bayeh and H.Baligh, "SCMA Codebook Design,"2014 IEEE 80th Vehicular Technology Conference (VTC2014-Fall),2014, pp.1-5, doi: 10.1109/VTCFall.2014.69666170.
The SCMA codebook design can also be considered through aspects of resource allocation, design factor graph, reduction of receiving end complexity, reduction of energy consumption and the like, the invention is different, and the innovation point of the invention is that the SCMA codebook design is converted into parameter optimization of user code words so as to reduce the error rate of an SCMA system.
The moth fire-fighting algorithm is a novel swarm intelligent optimization algorithm, is evolved from a natural moth flying navigation mechanism, adopts a spiral track in the optimization process, and ensures the searching capability of the algorithm in the global space. The arrangement of the moths and the flames is a final elimination mechanism, the number of flames in each iteration is reduced, and the full search of the algorithm in a local space is ensured. Mirjalli S. Moth-flame optimization algorithm A novel natural-embedded real estate [ J ]. Knowledge-Based Systems,2015,89(NOV.): 228-.
Disclosure of Invention
The invention aims to solve the technical problem of providing a method for searching user code word parameters in SCMA codebook design by using a moth fire-extinguishing algorithm in order to reduce the SCMA codebook design complexity.
The technical scheme adopted by the invention for solving the technical problems is that the SCMA codebook design method based on the moth fire suppression algorithm comprises the following steps:
1) determining J, M, N, K parameters in the SCMA codebook according to user requirements; j is the number of users, M is the length of user code words respectively, N is the dimension of the user code words, and K is the number of resource blocks; setting N to be 2 and K to be 4;
2) setting the user code words as follows:
Figure BDA0003268989290000021
determining 4 x d to be optimizedfA parameter is ai,
Figure BDA0003268989290000022
i＝1,2,...,2*df，
Figure BDA0003268989290000023
Representing the real number field, dfThe number of users multiplexed on the resource block.
3) Constructing a factor graph matrix F through a Latin criterion, wherein each row in the factor graph matrix has dfThe element is 1, then user code words are brought into the factor graph matrix F to obtain a factor graph structure matrix, and finally, part of the user code words in the factor graph structure matrix are selected to be rearranged to obtain an SCMA codebook to be optimized;
4) setting the number of dimensions in the moth fire-fighting algorithm as the number 4 x d of the parameters to be optimized by taking the SCMA codebook to be optimized as the criterion of the minimum bit error ratefObtaining an SCMA codebook to be optimized according to a parameter value to be optimized, setting the number of moths in the moth fire suppression algorithm as n, and starting iteration of the moth fire suppression algorithm:
4.1) taking the bit error rate f _ BER of the SCMA system to be optimized as the fitness of a moth fire suppression algorithm when the ratio EbN0 of the energy of each symbol to the spectral density of noise energy of the SCMA codebook to be optimized is a set value, initializing the positions of n moths, and calculating the fitness of each moth through the positions of the moths; the number of the initial flames is n, the positions are the positions of n moths, and the number of the flames is
Figure BDA0003268989290000031
Iter is the current iteration frequency, Iter is the maximum iteration frequency, and round is an integer function;
4.2) updating the position of the moth, recalculating f _ BER according to the updated position of the moth and arranging the f _ BER in an ascending order, taking the f _ BERs of the front flame _ num, and taking the position of the moth as the updated flame position if the f _ BER is smaller than the f _ BER of the current flame position; otherwise, the flame position remains unchanged; the position of the moth is a position coordinate, and the dimensionality is the number of parameters to be optimized;
4.3) reducing the number of flames and improving the local optimal solution; continuously updating the position of the moth until the maximum iteration number Iter is reached;
4.4) get the moth position that minimizes f _ BER to get the best SCMA codebook.
The method has the advantages that the method can be suitable for SCMA codebook design under different channels, and only SCMA channel parameters in the bit error rate function f _ BER are replaced under different channels; along with the increase of the number of users, the complexity of the moth fire suppression algorithm is slowly increased, and the realization is simple; according to the simulation result, the bit error rate of the codebook obtained by the method is obviously improved compared with other codebooks under the Gaussian channel and the Rayleigh channel.
Drawings
FIG. 1 is a flow chart of codebook design according to the present invention;
FIG. 2 is a factor graph according to the present invention;
FIG. 3 is a graph comparing bit error rates of the generated codebook and other codebooks in the Gaussian channel according to the embodiment;
FIG. 4 is a graph comparing bit error rates of the generated codebook and other codebooks in the Rayleigh channel according to the embodiment;
FIG. 5 is a graph comparing bit error rates of the generated codebook and other codebooks in the Gaussian channel according to the embodiment.
Detailed Description
The SCMA codebook design is regarded as the optimization of user code word parameters, and the optimized objective function is the bit error rate function of the SCMA system, namely:
Figure BDA0003268989290000032
Figure BDA0003268989290000033
wherein F _ BER represents a bit error rate function of the SCMA system, EbN0 represents a ratio of each symbol energy to noise energy spectral density in the SCMA codebook, F represents a factor graph matrix of the SCMA codebook, and CB ═ CB { (CB }1,CB2,...,CBJRepresents the codebook set of each user, J represents the number of users in the SCMA system, K represents the number of resource blocks, dfRepresenting the number of users, S, multiplexed on each resource blockiUser code word with length M of order N and representing energy normalization, E { | | Si||2Is the user codeword SiThe energy of (a).
Figure BDA0003268989290000041
The expression of (a) is as follows:
Figure BDA0003268989290000042
according to the factor graph matrix, a codebook is obtained, so the codebook design problem becomes:
Figure BDA0003268989290000043
wherein the content of the first and second substances,
Figure BDA0003268989290000044
the optimization target is set a and b, the fitness function of the moth fire suppression algorithm is the bit error rate function f _ BER of the SCMA system, the parameter set a and b to be optimized are initialized, each parameter is constrained within a limit range, n moth positions are randomly generated within the range, and the moth positions correspond to n SCMA codebooks. And solving the bit error rate of each codebook through the f _ BER, updating the iterative moth position and the flame position, and updating the SCMA codebook according to the bit error rate and the iterative moth position and the flame position until the maximum iteration number is reached to obtain the optimal SCMA codebook which minimizes the f _ BER.
As fig. 1 shows a specific design flow of the present invention, the following are set: the number of resource blocks is 4, the dimension of each user code word is 2, and the length is 4.
The step 1 is completed at the same time of the setting,
K＝4,N＝2,M＝4
number of users
Figure BDA0003268989290000045
Overload rate of system
Figure BDA0003268989290000046
In the step 2:
number of users multiplexed on resource block
Figure BDA0003268989290000047
The user codeword can be expressed as:
S1＝[a1+b1*j,a2+b2*j,-a2-b2*j,-a1-b1*j]
S2＝[a3+b3*j,a4+b4*j,-a4-b4*j,-a3-b3*j]
S3＝[a5+b5*j,a6+b6*j,-a6-b6*j,-a5-b5*j]
Figure BDA0003268989290000048
the number of the parameters to be optimized is 12; setting the number n of the moths in the moth fire-fighting algorithm to be 30;
in the step 3:
and constructing a factor graph matrix F through a Latin criterion.
Number of users multiplexed on resource block dfSince 3, the number of "1" in each row in the factor graph matrix is 3, one factor graph is shown in fig. 2, and the factor graph matrix F is as follows:
Figure BDA0003268989290000051
the user code words are brought into the factor graph matrix, and the factor graph structure matrix of the SCMA codebook can be obtained:
Figure BDA0003268989290000052
some of the user code words require a code word rearrangement to increase the inter-user diversity, the rearrangement rule being such that
Figure BDA0003268989290000053
The following steps are changed:
Figure BDA0003268989290000054
the factor graph structure matrix is updated to the form:
Figure BDA0003268989290000055
Siirepresents a pair SiThe code word rearrangement.
Obtaining an SCMA codebook to be optimized through user codeword rearrangement:
Figure BDA0003268989290000056
Figure BDA0003268989290000057
Figure BDA0003268989290000061
Figure BDA0003268989290000062
Figure BDA0003268989290000063
Figure BDA0003268989290000064
in the step 4, the specific process is as follows:
step 4.1: taking the bit error rate f _ BER of the SCMA system as the fitness of a moth fire suppression algorithm when the ratio EbN0 of the energy spectrum density of each symbol of the SCMA codebook to be optimized to a set value, initializing the positions of n moths, determining the number of the positions during initial iteration, and calculating the fitness of each moth according to the positions of the moths; the number of the initial flames is n, the positions are the positions of n moths, the initial position of the flames is the initial position of the moths, and the number of the flames is
Figure BDA0003268989290000065
Iter is the current iteration frequency, and Iter is the maximum iteration frequency;
step 4.2: updating the positions of the moths, recalculating the f _ BERs according to the updated positions of the moths, arranging the f _ BERs in an ascending order, taking the f _ BERs of the front frame _ num, and taking the position of the moth as the updated flame position if the f _ BER is smaller than the f _ BER of the current flame position; otherwise, the flame position remains unchanged; the position of one moth corresponds to one position coordinate, and the dimensionality of the position coordinate is the number of parameters to be optimized.
Step 4.3: the number of flames is reduced, and the local optimal solution is improved;
step 4.4: continuously updating the position of the moth until the maximum iteration number Iter is reached;
step 4.5: the moth position that minimizes f _ BER is found to be the best SCMA codebook.
The optimal SCMA codebook for six users and four resource blocks under Gaussian channel is obtained as follows:
Figure BDA0003268989290000071
Figure BDA0003268989290000072
Figure BDA0003268989290000073
Figure BDA0003268989290000074
Figure BDA0003268989290000075
Figure BDA0003268989290000076
the optimal SCMA codebook of six users and four resource blocks under the Rayleigh channel is obtained as follows:
Figure BDA0003268989290000077
Figure BDA0003268989290000078
Figure BDA0003268989290000081
Figure BDA0003268989290000082
Figure BDA0003268989290000083
Figure BDA0003268989290000084
the optimal SCMA codebook for fifteen users and six resource blocks under Gaussian channel is obtained as follows:
Figure BDA0003268989290000085
Figure BDA0003268989290000086
Figure BDA0003268989290000087
Figure BDA0003268989290000091
Figure BDA0003268989290000092
Figure BDA0003268989290000093
Figure BDA0003268989290000094
Figure BDA0003268989290000095
Figure BDA0003268989290000096
Figure BDA0003268989290000101
Figure BDA0003268989290000102
Figure BDA0003268989290000103
Figure BDA0003268989290000104
Figure BDA0003268989290000105
Figure BDA0003268989290000106
in order to show the performance of the codebook, the codebook obtained in the embodiment is compared with the following conventional codebook [4] [5] [6] [7 ].
[4]SCMA:massive connectivity&low latency[EB/OL].[2016-06-15] http:// www.innovateasia.com/5g/gp2.html.
[5] SCMA simple codebook design [ J ] under Gauss channel, computer application research, 2017,34(09): 2744-.
[6] Zhangtian, sparse code non-orthogonal multiple access system multi-user codebook study [ D ]. Shanghai traffic university, 2017.
[7] Liu heng.scma technology study [ D ] southeast university, 2018 in fifth generation mobile communication systems.
FIG. 3 is a comparison of bit error rates of an optimal SCMA codebook for six users and four resource blocks with an existing codebook [4] [5] [6] [7] in the Gaussian channel, FIG. 4 is a comparison of bit error rates of an optimal SCMA codebook for six users and four resource blocks with an existing codebook [4] [6] [7] in the Rayleigh channel, and the codebooks obtained in the Gaussian channel and the Rayleigh channel are superior to the existing codebook. Fig. 5 is a bit error rate comparison of the best SCMA codebook for fifteen users, six resource blocks, with the existing codebook [6] for the gaussian channel, since only [6] discloses the codebook for fifteen users, six resource blocks.

Claims (6)

1. The SCMA codebook design method based on the moth fire-fighting algorithm is characterized by comprising the following steps:
1) determining parameters J, M, N, K in an SCMA codebook according to user requirements; j is the number of users, M is the length of user code words respectively, N is the dimension of the user code words, and K is the number of resource blocks; setting N to be 2 and K to be 4;
2) setting the user code words as follows:
Figure FDA0003573476330000011
determining 4 x d to be optimizedfA parameter is
Figure FDA0003573476330000012
Figure FDA0003573476330000013
Representing the real number field, dfThe number of users multiplexed on the resource block, j represents an imaginary number;
3) constructing a factor graph matrix F through a Latin rule, wherein each row in the factor graph matrix has dfTaking each element as 1, bringing a user code word into the factor graph matrix F to obtain a factor graph structure matrix, and finally, selecting part of user code words in the factor graph structure matrix to be rearranged to obtain an SCMA codebook to be optimized;
4) setting the dimension of the moth fire suppression algorithm as the number 4 x d of the parameters to be optimized by taking the SCMA codebook to be optimized as the criterion of the minimum bit error ratefObtaining an SCMA codebook to be optimized according to a parameter value to be optimized, setting the number of moth positions in the moth fire suppression algorithm as n, and starting iteration of the moth fire suppression algorithm:
4.1) taking the bit error rate f _ BER of the SCMA system when the ratio EbN0 of each symbol energy to noise energy spectral density of the SCMA codebook to be optimized is a set value as the fitness of a moth fire-fighting algorithm, initializing the positions of n moths, and calculating the fitness of each moth according to the positions of the moths; the number of the initialized flames is n, the positions of the flames are the positions of n moths, and the number of the current flames, namely flame _ num, is
Figure FDA0003573476330000014
Iter is the current iteration frequency, Iter is the maximum iteration frequency, and round is an integer function;
4.2) updating the position of the moth, recalculating f _ BER according to the updated position of the moth and arranging the f _ BER in an ascending order, taking the f _ BERs of the front flame _ num, and taking the position of the moth as the updated flame position if the f _ BER is smaller than the f _ BER of the current flame position; otherwise, the flame position remains unchanged;
4.3) reducing the number of flames, and updating the positions of the moths until the maximum iteration number Iter is reached;
4.4) get the moth position that minimizes f _ BER and thus get the best SCMA codebook.
2. The method of claim 1, wherein the number n of moths in the moth-fire algorithm is set to 30.
3. The method of claim 1, wherein the codeword reordering rule is:
will be provided with
Figure FDA0003573476330000021
The following steps are changed:
Figure FDA0003573476330000022
4. the method of claim 1, wherein J is 6, K is 4, and d is dfWhen the factor graph matrix F is 3, the factor graph matrix F in step 3) is as follows:
Figure FDA0003573476330000023
factor graph structure matrix Fs：
Figure FDA0003573476330000024
5. The method as claimed in claim 4, wherein the user code words partially in the factor graph structure matrix selected in step 3) are rearranged, and the rearranged factor graph structure matrix Fs'：
Figure FDA0003573476330000025
SiiRepresents a pair SiI is 1,2, 3.
6. The method of claim 4, wherein the step 3) of obtaining the SCMA codebook to be optimized through user codeword rearrangement comprises:
Figure FDA0003573476330000026
Figure FDA0003573476330000027
Figure FDA0003573476330000031
Figure FDA0003573476330000032
Figure FDA0003573476330000033
Figure FDA0003573476330000034
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