SCMA codebook design method and communication method for non-ground network

Abstract

The application discloses a non-ground network-oriented SCMA codebook design method and a communication method, and belongs to the field of Internet of Things communication. f The codebook design method comprises the following steps: sorting users in ascending order of distance between the users and the nadir point of an air base station, allocating d f power factors to each orthogonal resource, and calculating 1≤i≤d f ; generating a set P composed of K-dimensional column vectors containing N 1s and K-N 0s, dividing d f orthogonal groups from the set P, and alternately arranging the remaining column vectors with the d i orthogonal groups to form a set P'; sorting q i in ascending order of p i , replacing the ith element 1 of each row of P' with q K×J , and sorting the column vectors in P' in ascending order of column vector power sum to obtain a signature matrix F K×J ; constructing SCMA codebooks of all users based on F K×J , calculating a worst error rate, taking the minimum of the worst error rate as an optimization target, solving corresponding parameters, and obtaining the SCMA codebooks of all users. The application can solve the user unfairness problem caused by channel difference in a non-ground network and realize offline optimization of an SCMA codebook.

Description

TECHNICAL FIELD

[0001] The application belongs to the field of Internet of Things communication, and more particularly relates to a SCMA codebook design method and a communication method for a non-terrestrial network. BACKGROUND

[0002] With the vigorous development of Internet of Things technology, the next generation of communication systems is committed to building a communication environment that can widely interconnect various Internet of Things devices, carry massive user data, and achieve efficient spectrum resource utilization. To realize the vision of 6G Internet of Things, current Internet of Things systems are actively expanding their service range and further using non-terrestrial network (Non-Terrestrial Network, NTN) infrastructure as a complementary means to expand global coverage and supplement the deficiencies of ground networks.

[0003] However, the traditional communication method based on orthogonal multiple access has difficulties in realizing large-scale connection because the number of orthogonal resources limits the total number of users that the system can accommodate. In order to solve the problem of short-time high concurrency communication in Internet of Things systems, SCMA (Sparse Code Multiple Access) emerges as a new type of code-domain non-orthogonal multiple access technology. SCMA directly maps the instantaneous input information of each user into a multi-dimensional code word in the sparse codebook for overlapping transmission, greatly improving the resource reuse rate and the number of concurrent access users. In addition, the performance of the SCMA system mainly depends on the sparse codebook design scheme, and a specific optimization scheme for the applicable scenario can effectively reduce multi-user interference and improve the system bit error rate performance.

[0004] Although SCMA is considered an effective solution to realize high-concurrency access of ground Internet of Things, unlike the fixed position of base stations in ground Internet of Things, air base stations in non-terrestrial networks have high mobility, and the corresponding channel scenarios also change. The existing SCMA codebook design method for ground Internet of Things has obvious channel differences and user service unfairness problems in the non-terrestrial network scenario. In addition, the hardware cost and power consumption are limited in non-terrestrial networks, and the existing SCMA codebook design method involves complex online optimization calculation, which cannot be effectively applied to non-terrestrial networks.

[0005] In summary, it is of great significance to propose an SCMA codebook design method that can effectively solve the channel difference and user fairness problems in non-terrestrial networks and realize offline optimization. SUMMARY

[0006] In response to the defects of the existing technology and the need for improvement, the present invention provides an SCMA codebook design method and a communication method for non-terrestrial networks. Its purpose is to propose an SCMA codebook design method that can effectively solve the channel differences and user fairness problems in non-terrestrial networks and can achieve offline optimization.

[0007] To achieve the above objectives, according to one aspect of the present invention, a SCMA codebook design method for non-terrestrial networks is provided, comprising:

[0008] Step S1: Construct a mother constellation consisting of N-dimensional dense constellation points The signature matrix F is constructed using the orthogonal cascade power allocation method. K×J ;

[0009] K and J represent the number of orthogonal resources and the number of users in the non-terrestrial network cell, respectively. The J users are sorted in ascending order according to the distance between the user and the nadir point of the aerial base station, and the signature matrix F K×J The j-th column vector in represents the connection relationship between the j-th user and each orthogonal resource after sorting, 1≤j≤J; the orthogonal cascade power allocation method includes the following steps:

[0010] S11: Allocate d for each orthogonal resource f Power factor ρ i , and calculate the constellation operator corresponding to each power factor 1≤i≤d f , d f represents the number of users sharing the same orthogonal resource, θ i represents the power factor ρ i The corresponding phase rotation angle;

[0011] S12: Generate a set P consisting of all K-dimensional column vectors containing N 1s and KN 0s randomly arranged, and divide d f orthogonal groups, and the remaining column vectors are recorded as set R; each orthogonal group is composed of It is composed of two orthogonal column vectors;

[0012] S13: Compare the column vectors in set R with d f Orthogonal groups are alternately arranged to form a new set P';

[0013] S14: Q i According to ρ i After sorting in ascending order, replace the i-th element 1 in each row of the set P' with the constellation operator q i , so that the column vectors in the set P' are sorted in ascending order according to the column vector power, and the sorted set P' is used as the signature matrix F K×J ;

[0014] Step S2: according to constructing an SCMA codebook set composed of SCMA codebooks of each user M represents the number of codewords in each SCMA codebook, and E represents the dimension energy of each SCMA codebook, denotes a signature matrix F K×J non-zero rows in the matrix and the corresponding rows in the mother constellation kronecker product;

[0015] Step S3: calculating the upper bound of the bit error probability of each user based on the SCMA codebook of each user, and taking the maximum value in it as the worst bit error rate;

[0016] Step S4: taking the minimum of the worst bit error rate as the optimization objective, taking the amplitude parameter δ of the mother constellation , d f power factors and d f phase rotation angles as optimization variables to be solved, establishing an optimization model, and solving the optimization model under the condition that the dimension energy of each SCMA codebook is unchanged, and then substituting the obtained optimization variables into to obtain the SCMA codebook of each user.

[0017] Further, in step S3, the upper bound of the bit error probability of each user based on the SCMA codebook of each user is calculated, including:

[0018] For the jth user, the corresponding pairwise error probability is calculated based on its SCMA codebook

[0019] The upper bound of the bit error probability of the jth user is calculated as:

[0020]

[0021] where P e,j represents the upper bound of the bit error probability of the jth user; X = [x1, x2,..., x J ] represents the transmission codeword set of J users, x j represents the transmission codeword of the jth user, represents the transmission codeword set obtained by incorrectly decoding the received transmission signal of the jth user, represents the transmission codeword of the jth user in the transmission codeword set . represents the number of error bits of the jth user.

[0022] Further, the channel model between the user and the air base station is modeled as a Rician channel model;

[0023] And the pairwise error probability of the jth user is The expression is:

[0024]

[0025] Where κ represents the Rice factor; Φ k is the set of users that collide on the kth orthogonal resource, x l [k] and Represent the user set Φ k The user's transmission codeword and the transmission codeword after decoding error; pl j is the path loss experienced by the jth user; N0 is the noise variance.

[0026] Furthermore, the path loss pl of the jth user is j for:

[0027]

[0028] Where H represents the height of the aerial base station, represents the mean distance between the jth user and the nadir point, and α≥1 is the path loss coefficient.

[0029] Furthermore, the mean distance of the jth user for:

[0030]

[0031] Wherein, a=j, b=J-j+1, Γ(·) represents a gamma function, and R represents the radius of the non-terrestrial network cell.

[0032] Furthermore, the mother constellation It is constructed based on pulse amplitude modulation and combined with suboptimal interleaving and permutation rules.

[0033] Furthermore, when N is an odd number, the mother constellation The N-dimensional dense constellation points in are:

[0034] A N =[-a M / 2 ,-a M / 2-1 ...,-a1,a1,...,a M / 2 ]

[0035] When N is an even number, the mother constellation The N-dimensional dense constellation points in are:

[0036] A N =[-a1,a M / 2 ,-a2,a M / 2-1 ,...,-a M / 2 ,a1]

[0037] wherein a m =(m(δ-1)+(2-δ)), m=1,2,...,M / 2; δ>1 represents the amplitude parameter of the parent constellation.

[0038] According to still another aspect of the present application, there is provided a computer program product comprising a computer program; the computer program, when executed by a processor, implements the above-mentioned SCMA codebook design method provided by the present application.

[0039] According to still another aspect of the present application, there is provided a communication method for a non-terrestrial network, comprising:

[0040] After the aerial base station maps the input information bits of each user into SCMA code words based on the SCMA codebook of each user and superimposes them, the aerial base station transmits the superimposed SCMA code words to each user terminal.

[0041] The SCMA codebook of each user is designed by the above-mentioned SCMA codebook design method provided by the present application.

[0042] According to still another aspect of the present application, there is provided a non-terrestrial network system, comprising: an aerial base station and a user terminal;

[0043] The transmission code word transmitted by the aerial base station to the user terminal is obtained by superimposing the SCMA code word of each user, and the SCMA code word of each user is obtained by mapping the information bits of each user based on the SCMA codebook.

[0044] The SCMA codebook of each user is designed by the above-mentioned SCMA codebook design method provided by the present application.

[0045] Overall, the above technical solutions conceived by the present application can achieve the following beneficial effects:

[0046] (1) The present application allocates the same power factor to each orthogonal resource, realizes power balance among different orthogonal resources, and improves the bit error rate performance of the system; when generating the signature matrix used to construct the SCMA codebook, the users are sorted in ascending order of distance, i.e., the users are sorted in ascending order of path loss, and the column vectors in the signature matrix are sorted in ascending order of column vector power sum, so that users with larger path loss will be allocated larger power, realizing user fairness; by introducing a proper constellation operator, the number of parameters to be optimized and solved is reduced from J+d f +1 to d f +d f +1, and d f ​The amplitude of the change with the non-ground network size is far less than the user number J, which effectively reduces the calculation complexity, and in addition, the optimization calculation only involves system configuration parameter information and known user proximity sorting information, and does not depend on online information, and can be optimized offline.

[0047] (2) The application combines large and small scale fading to model the different user NTN channel model, specifically, the channel between the user and the orthogonal resource is established based on the Rice distribution, reflecting the small scale fading between the user and the orthogonal resource, and the change rule of the distance between the general user and the air base station nadir point is combined to reflect the path loss of different users, and the channel model of the user is accurately established; based on the established NTN model, the multi-user codebook optimization is completed, and the system gain of the SCMA codebook is effectively improved. BRIEF DESCRIPTION OF DRAWINGS

[0048] Figure 1 It is a scene schematic diagram of the existing non-ground network;

[0049] Figure 2 It is a schematic diagram of the SCMA codebook design method for non-ground network provided by the embodiment of the application;

[0050] Figure 3 It is a bit error rate performance simulation diagram of different methods under 150% overload rate provided by the embodiment of the application; wherein (a) is the simulation result corresponding to the Rice factor K = 10, (b) is the simulation result corresponding to the Rice factor K = 2;

[0051] Figure 4 It is a bit error rate performance simulation diagram of different methods under 200% overload rate provided by the embodiment of the application. DETAILED DESCRIPTION

[0052] In order to make the purpose, technical scheme and advantages of the application clearer, the application will be further described in detail below in combination with the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the application, and are not used to limit the application. In addition, the technical features involved in each embodiment of the application described below can be combined with each other as long as they do not conflict with each other.

[0053] In the application, the terms "first", "second", etc. (if any) in the application and the drawings are used to distinguish similar objects, and do not necessarily describe a specific order or sequence.

[0054] Before explaining the technical scheme of the application in detail, the basic concepts related to non-ground network and SCMA codebook design are briefly introduced as follows.

[0055] To address the problem of short-term, high-concurrency communications in IoT systems, sparse code multiple access (SCMA) has emerged as a novel code-domain non-orthogonal multiple access technology. SCMA significantly improves resource reuse and the number of concurrent users by directly mapping each user's instantaneous input information into a multi-dimensional codeword in a sparse codebook and transmitting it in an overlapping manner. Furthermore, the performance of an SCMA system depends primarily on the sparse codebook design. Specific optimization schemes tailored to the applicable scenario can effectively reduce multi-user interference and improve system bit error rate performance.

[0056] The communication model of the non-terrestrial network downlink communication system based on SCMA is as follows: Figure 1 As shown in Figure 1, in this NTN cell, the airborne base station is located at the center of the cell and transmits information to J users through K orthogonal resource nodes, where the overload factor is defined as λ = J / K > 1. Assume that the cell is a circular area with a radius of R and users are randomly distributed within the cell. Each user is assigned a unique SCMA codebook, expressed as Contains M codewords of dimension K, then the process of mapping the transmission information bits of the jth user into codewords is f j : ie,x j =f j (b j ),in is the input bit information of user j, and is the transmitted codeword. Each codeword contains only N non-zero elements, and N < K. The arrangement of the user codebook depends on the signature matrix F K×J The element f in k,j represents the connection relationship between the kth orthogonal resource and the jth user, k∈{1,2,…,K}, j∈{1,2,…,J}. If and only if f k,j =1, there is a connection relationship between the kth orthogonal resource and the jth user.

[0057] In the signature matrix basis F K×J On the other hand, a mother constellation is constructed by N-dimensional dense constellation points. Afterwards, you can follow Construct a SCMA codebook set consisting of each user's SCMA codebook M represents the number of codewords in each SCMA codebook, and E represents the dimensional energy of each SCMA codebook; represents the energy normalization parameter; A special operation is defined, that is, the signature matrix F K×J The nth non-zero element of each column vector in The nth row in performs the Crocker inner product operation.

[0058] In the communication system, each orthogonal resource is d f For this reason, there must be at least d f Different phases are used to distinguish these users, and finally J+d f +1 parameter, namely d f phase rotation angles, J power parameters, and the mother constellation However, as the scale of non-terrestrial networks increases, the number of parameters that need to be designed will also increase, which will lead to an increase in the optimization complexity of codebook design and the performance of the codebook derived by the heuristic algorithm may deteriorate.

[0059] In non-terrestrial network scenarios, due to limited hardware costs and power consumption, it is necessary to reduce the number of optimization parameters. In addition, the power balance at different orthogonal resources needs to be considered, because if the power of a certain carrier is small, the codeword distance occupying the resource block will become smaller, which will lead to a significant reduction in decoding accuracy. In addition, the cells of non-terrestrial networks are much larger than those of terrestrial networks. Therefore, the differences in user locations in non-terrestrial network cells cannot be ignored. Such differences in location will lead to differences in path losses for different users. In addition, the movement of aerial base stations will cause frequent changes in user locations, which will cause the specific value of path loss to change at all times. It is impossible to complete codebook optimization for fixed path loss. When designing SCMA codebooks for non-terrestrial networks, it is also necessary to optimize the allocated power to achieve user fairness.

[0060] The following are examples.

[0061] Example 1:

[0062] A SCMA codebook design method for non-terrestrial networks, such as Figure 2 As shown, including:

[0063] Step S1: Construct a mother constellation consisting of N-dimensional dense constellation points The signature matrix F is constructed using the orthogonal cascade power allocation method. K×J ;

[0064] Step S2: Follow Construct a SCMA codebook set consisting of each user's SCMA codebook M represents the number of codewords in each SCMA codebook, E represents the dimensional energy of each SCMA codebook, represents the Kronecker product;

[0065] Step S3: Calculate the upper bound of the bit error probability of each user based on the SCMA codebook of each user, and take the maximum value as the worst bit error rate;

[0066] Step S4: establishing an optimization model with the amplitude parameter δ of the mother constellation, d f power factors and d f phase rotation angles as optimization variables to be solved, and solving the optimization model under the condition that the dimension energy of each SCMA codebook is unchanged, and then substituting the obtained optimization variables into to obtain the SCMA codebooks of the users.

[0067] The following will explain each step in detail.

[0068] Considering the characteristic of pulse amplitude modulation with symbol energy diversity, optionally, in step S1 of the embodiment, the mother constellation is constructed based on pulse amplitude modulation, combined with suboptimal interleaving and permutation rules;

[0069] When N is an odd number, the N-dimensional dense constellation points in the mother constellation are:

[0070] A N = [-a M / 2 , -a M / 2-1 ..., -a1, a1,..., a M / 2 ]

[0071] When N is an even number, the N-dimensional dense constellation points in the mother constellation are:

[0072] A N = [-a1, a M / 2 , -a2, a M / 2-1 ..., -a M / 2 , a1]

[0073] Wherein, a m = (m(δ-1)+(2-δ)), m = 1, 2,..., M / 2; δ>1 represents the amplitude parameter of the mother constellation to be optimized.

[0074] The energy of each codebook dimension based on the designed mother constellation is:

[0075]

[0076] K and J respectively represent the number of orthogonal resources and the number of users in the non-terrestrial network cell; in order to realize the fairness of user service, before constructing the signature matrix F K×J using the orthogonal layer combined power allocation method, the J users in the non-terrestrial network cell will be sorted in ascending order according to the distance between the user and the nadir point of the air base station, and the constructed signature matrix F​K×J The columns of the matrix F are sorted in ascending order of column vector power sum. It is easy to understand that the greater the distance between the user and the nadir point of the air base station, the greater the path loss, and the greater the power of the jth column vector in the signature matrix F K×J of the user. Therefore, the embodiment can allocate greater power to users with greater path loss to achieve user fairness.

[0077] Due to the high-speed mobility of the air base station, the relative positions between the base station and the users in the non-terrestrial Internet of Things are always changing, i.e., the position of the jth user relative to the nadir point of the air base station is unknown. However, the user proximity relationship can be known through the size of the uplink received signal power, so the user proximity sorting is known information for the downlink system.

[0078] In order to achieve power balance between different orthogonal resources and effectively reduce the computational complexity, in the embodiment, the orthogonal layer joint power allocation method for constructing the signature matrix F K×J includes the following steps:

[0079] S11: allocate d f power factors p i to each orthogonal resource and calculate the constellation operator corresponding to each power factor p 1≤i≤d f , d f represents the number of users sharing the same orthogonal resource, and q i represents the phase rotation angle corresponding to the power factor p i ;

[0080] The constellation operator represents changing the power and phase of the generated constellation point to distinguish the signals of different users; based on the introduction of the above-mentioned constellation operator q i , the orthogonal resource and the constellation operator need to be allocated to each user to complete the user codebook construction, which follows the following principles: preferentially allocating greater power to users with greater propagation loss to achieve user fairness; each resource block has the same power factor to achieve power balance between different resource blocks.

[0081] Specifically, some users in SCMA are divided into d f orthogonal groups, and all users in the group are guaranteed to occupy orthogonal resources, and the remaining users are in a group alone. Considering the power balance between different resource nodes, each group should be allocated the same q i ;

[0082] S12: generate a set P consisting of K-dimensional column vectors containing N 1s and K-N 0s, at this time, the total number of column vectors P in the set is J; divide df orthogonal groups, and the remaining column vectors are denoted as set R; each orthogonal group consists of two orthogonal column vectors;

[0083] S13: The column vectors in set R are alternately arranged with the d f orthogonal groups to form a new set P';

[0084] S14: The q i column vectors in set P' are sorted in ascending order of the column vector power sum, and the sorted set P' is taken as the signature matrix F i . i K×J ;

[0085] For the jth column in set P', the column vector power sum is calculated as follows:

[0086] In step S3, the calculation of the upper bound of the bit error probability of each user depends on the specific channel model.

[0087] Traditional SCMA codebooks for ground IoT mainly consider Gaussian channels or Rayleigh channels, ignoring large-scale fading (path loss) and the problem of the simultaneous existence of direct and non-direct paths in small-scale fading. Unlike ground IoT, there is a large direct path component between the user terminals and the air base station in non-ground network cells. Therefore, the traditional design method cannot accurately depict the channel model between the user terminals and the air base station in non-ground network cells. To solve this problem, the present embodiment uses a Rice distribution for channel modeling. Specifically, let be the channel between the air base station and the jth user, and each component h j,k denote the channel between the kth orthogonal resource and the jth user, which is further denoted as where g j,k is modeled as a Rice fading channel, subject to a Rice distribution with a Rice factor κ, d j is the distance between the air base station and the jth user, and α ≥ 1 is the path loss coefficient. The channel h j,k established based on the Rice distribution reflects the small-scale fading of the channel. The signal sent by the base station to the user j in the downlink is where p l denotes the power allocated to the lth user, n j is the noise of the jth user, and n j obeys a Gaussian distribution with a mean of 0 and a variance of N0.

[0088] ​With the information of the known user's rank, the relative distance of J users can be measured by the expectation of the order statistics, and the general law of the large-scale fading variation in non-terrestrial networks can be obtained.

[0089] In the polar coordinate system with the nadir point as the origin, the position of user j can be characterized by the tensor angle and the distance r j from the center. After the users are ranked from the nearest to the farthest, the distances from the center to the J users form an independent and identically distributed random sequence r1≤r2≤,...,≤r J , where the mean distance of the jth user is Γ(·) represents the gamma function, a = j and b = J - j + 1, and the path loss of user j is d j , where d is the distance between the air base station and the jth user, and a ≥ 1 is the path loss coefficient.

[0090] The transmission codeword of the J users is defined as X = [x1, x2,..., x J ], and if the transmission signal X of the jth user is incorrectly decoded as another set of codewords , the pairwise error probability is:

[0091]

[0092] where X = [x1, x2,..., x J ] represents the set of transmission codewords of the J users, x j represents the transmission codeword of the jth user, represents the set of transmission codewords obtained by incorrectly decoding the received transmission signal of the jth user, represents the transmission codeword of the jth user in the set of transmission codewords ; κ represents the Rice factor; Φ k represents the set of users that collide on the kth orthogonal resource, x l [k] and represent the transmission codeword and the decoded error transmission codeword of the users in the user set Φ k ; pl j represents the path loss experienced by the jth user; and N0 represents the noise variance.

[0093] It should be emphasized that for the theoretical bit error rate of a single-user codebook, only when the user's transmitted information is incorrectly decoded is it considered. That is, the upper bound of the bit error probability of the jth user is where represents the number of error bits of user j.

[0094] Based on the calculated average bit error rate and worst bit error rate of J users are solved as

[0095] The channel states experienced by different users are different, resulting in different quality of service provided by the base station to each user in the Internet of Things system, and in addition, according to the short board effect, the average performance of the Internet of Things system is most affected by the worst user codebook performance, so by using the uneven distribution of power to balance the difference in loss experienced by different users, the overall system performance is improved under the premise of ensuring user fairness. Correspondingly, step S4 of the embodiment takes the above-mentioned worst bit error rate as the optimization target when establishing an optimization model to solve related parameters.

[0096] In step S4 of the embodiment, the optimization model can be represented as:

[0097]

[0098] It is easy to understand that this problem has the following constraints:

[0099]

[0100] ρ i > 0, 1≤i≤d f

[0101] 0 < θ i < π, 1≤i≤d f

[0102] In the embodiment, the optimization variables finally solved are d f power factors and d f phase parameters and amplitude parameters δ in the parent constellation A, a total of d f +d f +1, since d f is less than J, and the growth rate of d f is much smaller than the growth rate of the number of users in the non-terrestrial network cell, so the embodiment effectively reduces the computational complexity of the SCMA codebook design.

[0103] In addition, in the embodiment, the optimization calculation only involves system configuration parameter information and known user distance sorting information, and does not depend on online information, so the SCMA codebook design method provided by the embodiment can be executed offline, and the SCMA codebook is generated and directly deployed in the non-terrestrial network Internet of Things system sender.

[0104] Alternatively, in the embodiment, the genetic algorithm is used to solve the optimization problem, the population size is set to 50, the maximum number of iterations is limited to 20 times, and the final user codebook is obtained.

[0105] Although the final generated codebooks of the embodiment can vary in specific numerical values, they have similar theoretical pair error probability values and show superior bit error rate performance in system performance and user fairness simulation.

[0106] In general, the embodiment can generate codebooks offline and directly deploy them in the IoT system transmitter of the non-terrestrial network, solve the problems of high online optimization complexity and user service unfairness of existing codebooks, and effectively alleviate the channel difference problem caused by high-speed movement of the air base station, and is especially suitable for narrowband non-terrestrial IoT downlink communication systems.

[0107] Embodiment 2

[0108] A computer program product includes a computer program; the computer program is executed by a processor to implement the SCMA codebook design method provided in the above embodiment 1.

[0109] Embodiment 3

[0110] A communication method for a non-terrestrial network, comprising:

[0111] After the air base station maps the input information bits of each user to SCMA code words based on the SCMA codebook of each user and superimposes them, the air base station transmits them to each user terminal;

[0112] The SCMA codebook of each user is designed by the SCMA codebook design method provided in the above embodiment 1.

[0113] Embodiment 4

[0114] A non-terrestrial network system, comprising: an air base station and a user terminal;

[0115] The transmission code word transmitted by the air base station to the user terminal is obtained by superimposing the SCMA code word of each user, and the SCMA code word of the user is obtained by mapping the information bits of the user based on the SCMA codebook;

[0116] The SCMA codebook of each user is designed by the SCMA codebook design method provided in the above embodiment 1.

[0117] The following compares the downlink SCMA system performance of the existing golden angle codebook (GAM), Star-QAM codebook, Chen codebook, Huang codebook, and Li codebook, to further verify the beneficial effects that can be achieved by the SCMA codebook design method provided in the embodiment of the application relative to the prior art.

[0118] Figure 3 The figure shows the bit error performance simulation of the SCMA codebooks designed by the six different methods when the overload rate is 150%.Figure 3 In the figure, the abscissa represents the signal-to-noise ratio, in dB, and the ordinate represents the worst bit error rate of each user in the system. For ease of display, Figure 3 In the figure, the SCMA codebook designed by the codebook design method provided by the application is referred to as "Prop.". In the figure, Figure 3 In the figure, the parameter setting is that the number of transmitting antennas and the number of receiving antennas are both 1, the ratio of the height of the air base station to the cell radius is 1, the modulation order of the codebook is 4, the path loss factor is α = 3, the codebook overload rate is 150%, and the positions of the users in the cell are subject to uniform distribution. Figure 3 In (a) of the figure, the Rician factor is κ = 10. Figure 3 In (b) of the figure, the Rician factor is κ = 2. According to the results shown in the figure, Figure 3 It can be known from the results shown in the figure that the worst bit error rate of the application is always better than that of other methods, which shows that the codebook designed by the SCMA codebook design method for non-terrestrial networks provided by the application has better system performance.

[0119] Figure 4 The figure shows the bit error performance simulation diagram of the SCMA codebooks designed by different methods when the overload rate is 200%. Since the bit error performance under the 200% overload rate is not included in the Huang codebook and the Chen codebook in the public data, the bit error performance of the Huang codebook and the Chen codebook is not shown in the figure. Figure 4 In the figure, only the bit error performance simulation results of the remaining three design methods (i.e., the golden angle codebook, the Star-QAM codebook, and the Li codebook) and the codebook design method provided by the application are shown. Figure 4 In the figure, the abscissa represents the signal-to-noise ratio, in dB, and the ordinate represents the worst bit error rate or the average bit error rate of each user in the system. In the figure, Figure 4 In the figure, the parameter setting is that the number of transmitting antennas and the number of receiving antennas are both 1, the ratio of the height of the base station to the cell radius is 1, the modulation order of the codebook is 4, the path loss factor is α = 3, the Rician factor is κ = 10, the codebook overload rate is 200%, and the positions of the users in the cell are subject to uniform distribution. Figure 4 It can be known from the results shown in the figure that the codebook designed by the SCMA codebook design method for non-terrestrial networks provided by the application is better than other methods in terms of the worst bit error rate and the average bit error rate, and the difference between the worst bit error rate and the average bit error rate is the smallest, which shows that the application has better user fairness and system performance.

[0120] Those skilled in the art can easily understand that the above description is only a preferred embodiment of the application and is not intended to limit the application, and any modification, equivalent replacement, and improvement made within the spirit and principle of the application shall be included in the protection scope of the application.

Claims

1. A SCMA codebook design method for non-terrestrial networks, characterized in that: include: Step S1: Construct a mother constellation consisting of N-dimensional dense constellation points The signature matrix F is constructed using the orthogonal cascade power allocation method. K×J ; K and J represent the number of orthogonal resources and the number of users in the non-terrestrial network cell, respectively. The J users are sorted in ascending order according to the distance between the user and the nadir point of the aerial base station, and the signature matrix F K×J The j-th column vector in represents the connection relationship between the j-th user and each orthogonal resource after sorting, 1≤j≤J; the orthogonal cascade power allocation method includes the following steps: S11: Allocate d to each orthogonal resource f Power factor ρ i , and calculate the constellation operator corresponding to each power factor d f represents the number of users sharing the same orthogonal resource, θ i represents the power factor ρ i The corresponding phase rotation angle; S12: Generate a set P consisting of all K-dimensional column vectors containing N 1s and KN 0s randomly arranged, and divide d f orthogonal groups, and the remaining column vectors are recorded as set R; each orthogonal group is composed of It is composed of two orthogonal column vectors; S13: Compare the column vectors in set R with d f Orthogonal groups are alternately arranged to form a new set P'; S14: Q i According to ρ i After sorting in ascending order, replace the i-th element 1 in each row of the set P' with the constellation operator q i , so that the column vectors in the set P' are sorted in ascending order according to the column vector power, and the sorted set P' is used as the signature matrix F K×J ; Step S2: Follow Construct a SCMA codebook set consisting of each user's SCMA codebook M represents the number of codewords in each SCMA codebook, E represents the dimensional energy of each SCMA codebook, Denotes the signature matrix F K×J The non-zero rows in the parent constellation Kronecker products of corresponding rows in ; Step S3: Calculate the upper bound of the bit error probability of each user based on the SCMA codebook of each user, and take the maximum value as the worst bit error rate; Step S4: Taking the worst bit error rate as the optimization goal, the mother constellation The amplitude parameters δ, d f power factor and d f The phase rotation angle is the optimization variable to be solved, and the optimization model is established. The optimization model is solved while ensuring that the dimensional energy of each SCMA codebook remains unchanged, and the obtained optimization variable is inserted into Get the SCMA codebook of each user.

2. The SCMA codebook design method for non-terrestrial networks according to claim 1, wherein: In step S3, the upper bound of the bit error probability of each user is calculated based on the SCMA codebook of each user, including: For the jth user, the corresponding pairwise error probability is calculated based on its SCMA codebook The upper bound of the bit error probability of the jth user is calculated as: Among them, P e,j represents the upper bound of the bit error probability of the jth user; X=[x1,x2,...,x J ] represents the transmission codeword set of J users, x j represents the transmission codeword of the jth user, represents the set of transmission codewords obtained after the transmission signal received by the jth user is decoded incorrectly, Represents the set of transmitted codewords The transmission codeword of the jth user in; represents the number of error bits of the jth user.

3. The SCMA codebook design method for non-terrestrial networks according to claim 2, wherein: The channel model between the user and the aerial base station is modeled as the Rice channel model; And, the pairwise error probability of the jth user is The expression is: Where κ represents the Rice factor; Φ k is the set of users that collide on the kth orthogonal resource, x l [k] and Represent the user set Φ k The user's transmission codeword and the transmission codeword after decoding error; pl j is the path loss experienced by the jth user; N0 is the noise variance.

4. The SCMA codebook design method for non-terrestrial networks according to claim 3, wherein: The path loss pl of the jth user j for: Where H represents the height of the aerial base station, represents the mean distance between the jth user and the nadir point, and α≥1 is the path loss coefficient.

5. The SCMA codebook design method for non-terrestrial networks according to claim 4, characterized in that: The mean distance of the jth user for: Wherein, a=j, b=J-j+1, Γ(·) represents a gamma function, and R represents the radius of the non-terrestrial network cell.

6. The SCMA codebook design method for non-terrestrial networks according to any one of claims 1 to 5, characterized in that: The mother constellation It is constructed based on pulse amplitude modulation and combined with suboptimal interleaving and permutation rules.

7. The SCMA codebook design method for non-terrestrial networks according to claim 6, wherein: When N is an odd number, the mother constellation The N-dimensional dense constellation points in are: A N =[-a M / 2 ,-a M / 2-1 ...,-a1,a1,...,a M / 2 ] When N is an even number, the mother constellation The N-dimensional dense constellation points in are: A N =[-a1,a M / 2 ,-a2,a M / 2-1 ,...,-a M / 2 ,a1] Among them, a m =(m(δ-1)+(2-δ)), m=1,2,...,M / 2; δ>1 indicates the mother constellation Amplitude parameter.

8. A computer program product, characterized in that The method comprises a computer program; when the computer program is executed by a processor, the method for designing the SCMA code according to any one of claims 1 to 7 is implemented.

9. A communication method for non-terrestrial networks, characterized in that: include: The airborne base station maps each user's input information bits into SCMA codewords based on each user's SCMA codebook, superimposes them, and transmits them to each user terminal; The SCMA codebook of each user is designed by the SCMA codebook design method according to any one of claims 1 to 7.

10. A non-terrestrial network system, characterized in that: Including: aerial base station and user terminal; The transmission codeword transmitted by the aerial base station to the user terminal is obtained by superimposing the SCMA codewords of each user, and the SCMA codeword of the user is obtained by mapping the user's information bits based on the SCMA codebook; The SCMA codebook of each user is designed by the SCMA codebook design method according to any one of claims 1 to 7.

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