WO2024078068A1 - 基于列表球形译码的otfs—scma系统低复杂度信号检测方法 - Google Patents

基于列表球形译码的otfs—scma系统低复杂度信号检测方法 Download PDF

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WO2024078068A1
WO2024078068A1 PCT/CN2023/106807 CN2023106807W WO2024078068A1 WO 2024078068 A1 WO2024078068 A1 WO 2024078068A1 CN 2023106807 W CN2023106807 W CN 2023106807W WO 2024078068 A1 WO2024078068 A1 WO 2024078068A1
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points
symbol
candidate set
information
auxiliary calculation
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PCT/CN2023/106807
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French (fr)
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王�华
康子奇
何东轩
杨天成
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北京理工大学
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
    • H04L25/03006—Arrangements for removing intersymbol interference
    • H04L25/03178—Arrangements involving sequence estimation techniques
    • H04L25/03203—Trellis search techniques
    • H04L25/03242—Methods involving sphere decoding
    • 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
    • H04L1/0052—Realisations of complexity reduction techniques, e.g. pipelining or use of look-up tables

Definitions

  • the present invention belongs to the field of communication technology, and in particular relates to a low-complexity signal detection method applied to an OTFS-SCMA system.
  • OTFS Orthogonal Time Frequency Space
  • OFDM Orthogonal Frequency Division Multiplexing
  • the basic principle of the classic MPA detector is to abstract several observation symbols y and transmission symbols x into observation nodes and variable nodes respectively, connect the observation nodes and variable nodes with edges according to the equivalent input-output relationship, and then draw the corresponding factor graph.
  • the Sum Product Algorithm (SPA) is used on the factor graph to calculate the transmitted message, and the symbol-by-symbol detection is completed after a preset number of iterations.
  • SPA Sum Product Algorithm
  • the calculation and transmission of messages are generally mapped to the logarithmic domain.
  • the message passed from the observation node to the variable node can be expressed as:
  • the message passed from the variable node to the observation node can be expressed as:
  • the posterior probability can be expressed as:
  • the log-likelihood ratio can be further obtained through (3), thereby recovering the corresponding bit information.
  • MPA detector in the uplink OTFS-SCMA system can ensure good multi-user detection performance, as the number of multipaths in the time-varying multipath channel in the scene increases, the more complex actual channel will cause the computational complexity of the MPA detector to increase exponentially. The uncontrollable complexity makes it difficult to apply the classic MPA detector at the receiving end of the OTFS-SCMA system.
  • the improved LSD-MPA detector can ensure good bit error rate performance while significantly reducing the computational complexity.
  • the factor matrix used for MPA detection in the OTFS-SCMA system is different from that of OFDM-SCMA.
  • the former is extracted from the channel state information of the actual uplink multi-user equivalent channel in the scene, while the latter is obtained by the SCMA codebook design scheme.
  • the factor matrix of OTFS-SCMA is more complex, and the value of d v may be much larger than the factor matrix corresponding to a well-designed SCMA codebook.
  • the present disclosure provides a low-complexity detection method for a delay-Doppler domain sparse code division multiple access system based on a list sphere decoding algorithm, which can significantly reduce the complexity of traditional MPA while ensuring basically consistent bit error rate performance.
  • the OTFS-SCMA system low-complexity detection method based on the list sphere decoding algorithm provided in the present disclosure mainly includes the following steps:
  • Step 1 In the uplink OTFS-SCMA system, the LSD-based MPA detection method is applied, that is, the list sphere decoding algorithm is used to search and obtain a simplified candidate set of calculation points for each observation symbol, thereby significantly reducing the computational complexity of multi-user detection in the existing system.
  • the information bit b that the user needs to transmit is equivalently mapped to the constellation vector u according to the mapping rule of Quadrature Amplitude Modulation (QAM), the corresponding relationship between the user's sparse codeword x and the constellation vector u is determined, and the mapping matrix G between the codebook and the constellation vector is obtained by inversion;
  • QAM Quadrature Amplitude Modulation
  • the corresponding rows and columns of G are deleted, compressed and inserted into the equivalent input-output relationship to obtain a new equivalent channel matrix H G , and then the equivalent input-output relationship between the receiving end observation vector y and the transmitting end constellation vector u is obtained, and then the corresponding factor matrix is abstracted, and the connection relationship between each observation symbol y g and the constellation vector u is determined to obtain the corresponding constellation vector combination u g ;
  • Step 2 based on the auxiliary calculation points, the MPA detection method based on LSD is supplemented, that is, auxiliary calculation points are selected from the points calculated by LSD and added to the candidate set to supplement the necessary codeword information missing from the candidate set.
  • T is the candidate set of calculation points
  • T is the candidate set of calculation points
  • the size of the LSD can significantly reduce the complexity, this simplification will cause the message iteration of the MPA detector to not converge.
  • This problem is mainly due to the fact that LSD searches and simplifies symbol by symbol, and finally determines the T closest to the observed symbol y g. points, but did not consider that the T points required to calculate the next observed symbol y f may require information from points other than the T points determined on y g , which is required by the basic rule of the MPA detector for message iteration on the factor graph.
  • the resulting lack of necessary information is reflected in the logarithmic domain, that is, the value of the corresponding missing message is - ⁇ .
  • the present invention utilizes the points searched in the LSD process and the corresponding distances calculated to select and add a small number of auxiliary calculation points, thereby ensuring the accuracy of the detection results as much as possible while controlling the impact on the complexity of LSD-MPA to a negligible level.
  • the candidate set is sorted using the one-to-one correspondence between sparse codewords and constellation vectors.
  • the comprehensiveness of the codeword information is judged to confirm whether the constellation vector combination u g in the set contains all the information of the codebook of the corresponding user symbol to the minimum extent (each codeword is included at least once):
  • Step 3 After completing the list sphere decoding search and supplementing the auxiliary calculation points for all observed symbols, the obtained calculation point candidate set is sent to the MPA detector for detection.
  • the present disclosure reduces the computational complexity of traditional MPA detection by introducing a list spherical decoding algorithm in the OTFS-SCMA uplink system; and improves the convergence of the detector by introducing a controllable number of auxiliary calculation points to supplement and update the list spherical decoding search results, thereby ensuring that the same detection accuracy as traditional MPA detection is obtained while the computational complexity is significantly reduced, thereby constructing a complete low-complexity detection method for the OTFS-SCMA system based on LSD.
  • the beneficial effects of the present disclosure are: (1) significantly reducing the computational complexity of traditional MPA detection in the OTFS-SCMA system; (2) by The supplementation and updating of search results ensure that the complexity is significantly reduced while obtaining the same detection accuracy as traditional MPA detection, achieving a more reasonable compromise between complexity and detection performance.
  • Figure 1 is the overall block diagram of the uplink OTFS-SCMA system
  • FIG2 is a flow chart of a low-complexity detection method according to the present disclosure.
  • Fig. 3 is a schematic diagram of an updating method for adding auxiliary calculation points
  • FIG4 is a comparison of detection performances of a low complexity detector according to the present disclosure and a conventional MPA detector
  • FIG. 5 is a comparison of the computational complexity performance of the low complexity detector according to the present disclosure and the traditional MPA detector.
  • the present disclosure provides a low-complexity detection method for a sparse code division multiple access system in a delay-Doppler domain.
  • the main idea of the invention is: by introducing a list sphere decoding algorithm into a classic MPA detector of an uplink OTFS-SCMA system, the amount of calculation of the message transmitted from the observation node to the variable node in the MPA detector is reduced, thereby reducing the computational complexity of the overall system; by reasonably selecting and adding auxiliary calculation points to the candidate calculation point set obtained by searching the list sphere decoding algorithm, the convergence of the detector is improved, a reasonable compromise between detection performance and complexity is achieved, and the transmission performance is further improved.
  • FIG1 shows an exemplary overall structure of an uplink OTFS-SCMA system using a low-complexity detector.
  • the number of system subcarriers is M
  • the subcarrier spacing is ⁇ f
  • the number of symbols is N
  • the symbol duration is Ts
  • the number of access users is J
  • the number of multipaths contained in the uplink delay-Doppler channel of the jth user is Pj .
  • a low-complexity detection method disclosed in the present disclosure mainly comprises the following steps:
  • Step 1 In the uplink OTFS-SCMA system, the LSD-based MPA detection method is applied, that is, the list sphere decoding algorithm is used to search and obtain a simplified calculation point candidate set for each observation symbol.
  • the specific method is as follows:
  • the information bit b that the user needs to transmit is equivalently mapped to the constellation vector u according to the mapping rule of Quadrature Amplitude Modulation (QAM), the corresponding relationship between the user's sparse codeword x and the constellation vector u is determined, and the mapping matrix G between the codebook and the constellation vector is obtained by inversion;
  • QAM Quadrature Amplitude Modulation
  • the corresponding rows and columns of G are deleted, compressed and inserted into the equivalent input-output relationship to obtain a new equivalent channel matrix H G , and then the equivalent input-output relationship between the receiving end observation vector y and the transmitting end constellation vector u is obtained, and then the corresponding factor matrix is abstracted, and the connection relationship between each observation symbol y g and the constellation vector u is determined to obtain the corresponding constellation vector combination u g ;
  • Step 2 Based on the auxiliary calculation points, the MPA detection method based on LSD is supplemented, that is, auxiliary calculation points are selected from the points calculated by LSD and added to the candidate set to supplement the necessary codeword information missing in the candidate set; the specific method is as follows:
  • the candidate set is sorted using the one-to-one correspondence between sparse codewords and constellation vectors.
  • the comprehensiveness of the codeword information is judged to confirm whether the constellation vector combination u g in the set contains all the information of the codebook of the corresponding user symbol to the minimum extent (each codeword is included at least once):
  • Step 3 After completing the list sphere decoding search and supplementing the auxiliary calculation points for all observed symbols, the obtained calculation point candidate set is sent to the MPA detector for detection.
  • a low-complexity detection method described in the present disclosure mainly comprises the following steps:
  • Step 1 Use the list sphere decoding algorithm to obtain a simplified candidate set of calculation points:
  • the equivalent input-output relationship between the delay-Doppler domain observation symbol yg and the constellation vector combination ug (vector length is L) composed of multiple user symbols connected to it is confirmed, and the factor matrix F (row weight is dv ) is abstracted to obtain the equivalent channel vector HGg ; then the observation symbol yg and the equivalent channel vector HGg are expanded into a column vector and a column full rank matrix with a length of (L+1) respectively.
  • ⁇ >0 IL is the L-order unit matrix; then Perform QR decomposition:
  • the hypersphere radius C of the list spherical decoding algorithm is set to + ⁇ , and each element in the constellation vector combination u g is searched from the Lth layer to the first layer in a backward recursive manner.
  • the Euclidean distance between them and the observed symbol y g is calculated to update the value of the radius C in real time.
  • the T constellation vector combinations with the closest distance are recorded as the candidate point set to be sent to the MPA detector for calculation (1).
  • the Euclidean distances d( ug ) corresponding to all searched points in the entire search process are recorded (if the search has not reached the first layer, partial Euclidean distances are recorded).
  • Step 2 Calculate the candidate set of points Determine whether additional auxiliary calculation points are needed:
  • T constellation vector combinations contain all the symbols of each user sparse codewords (each codeword is included at least once), then the candidate set of points is calculated No additional operations are required;
  • the judgment and calculation of the auxiliary calculation points may be performed after completing the LSD search and simplification of each observation symbol, or may be performed after completing the search and simplification of all observation symbols.
  • Step 3 Combine candidates, that is, according to step 2 , and construct the auxiliary calculation point combination to be added:
  • Step 4 Arrange your selections:
  • the corresponding results that have been searched and recorded by LSD are obtained
  • the Euclidean distance between most points and the actual observed symbol y g is calculated, and a small number of uncalculated points are calculated and recorded in this step.
  • the merge sorting method with lower complexity is used to sort All the constellation vector combinations in are sorted from large to small by Euclidean distance, and the point with the closest distance is selected and added to and delete All combinations containing the corresponding codewords (if only one is left, it will not be deleted).
  • FIG3 shows a schematic diagram of the method for adding auxiliary calculation points to update the candidate point set in the present disclosure. For example, assuming that (3, 4, 1) is For points that are close in distance, the updated At this point, user 2 and user 3 already have all the necessary information, and user 1 still lacks the information of the fourth codeword. Repeat the sorting and extract the point with the smallest distance to join Assume that the constellation vector combination (4, 4, 2) is the set The point with the smallest distance among all the remaining points is finally updated. The last two constellation vector combinations added This ensures that Contains comprehensive codeword information.
  • Step 5 After completing the list sphere decoding of all observed symbols, checking and adding necessary auxiliary calculation points, the updated calculation point candidate set is substituted into the traditional MPA detector for message iterative update. After the set maximum number of iterations I ter or the algorithm has converged, the posterior probability of all user sent symbols is output through (3) and the LLR is calculated, and the bit information is finally recovered.
  • step 2 in the aforementioned embodiment "supplementing the LSD-based MPA detection method based on auxiliary calculation points, that is, selecting auxiliary calculation points from the points calculated by LSD and adding them to the candidate set to supplement the necessary codeword information missing from the candidate set" is described as: step 2, step 3, step 4, and is explained.
  • the low-complexity detector based on auxiliary calculation points proposed in the present disclosure sets the T value to 400, which reduces the number of full traversal points calculated by the traditional MPA detector.
  • the total number of points is too different from the number of points for simplified calculation, only using LSD to reduce complexity without checking the missing of necessary information will lead to significant bit error rate performance loss, while only adding up to This problem can be avoided significantly by using an auxiliary calculation point.
  • the low-complexity detector based on auxiliary calculation points proposed in the present disclosure has significantly lower complexity than the traditional MPA detector.
  • the proposed detector has a significant difference in T value and the number of full traversal points.
  • the ratio is 2000/65536 ⁇ 3%, and the detection performance is basically the same at high signal-to-noise ratio, while the overall computational complexity can still be reduced by more than 75%.
  • the present disclosure introduces the list spherical decoding technology into the OTFS-SCMA system, reduces the amount of message calculations that the traditional MPA detector calculates to pass from the observation node to the variable node, thereby significantly reducing the overall detection complexity of the system, making the application of MPA detectors with good performance more practical; further, if it is used directly in the case of a large reduction in the amount of calculation, the problem of detector iterative divergence caused by the lack of necessary codeword information may occur, resulting in a large loss in detection performance, and by strategically searching and adding a small number of auxiliary calculation points, it will be possible to ensure that the complexity is significantly reduced while the loss of detection performance can still be suppressed to a negligible level, thereby achieving a reasonable compromise between detection performance and complexity and improving transmission performance.
  • the present invention discloses a low-complexity detection method applied to an OTFS-SCMA system, which introduces a list sphere decoding algorithm in the OTFS-SCMA uplink system to reduce the computational complexity of traditional MPA detection; introduces a controllable number of auxiliary calculation points to supplement and update the list sphere decoding search results, improves the convergence of the detector, and ensures that the same detection accuracy as traditional MPA detection is obtained while the computational complexity is significantly reduced.
  • the present invention has good industrial applicability.

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Abstract

本发明公开提供了一种应用于OTFS-SCMA系统的低复杂度检测方法，该方法在OTFS-SCMA上行系统引入列表球形译码算法，降低传统MPA检测的计算复杂度；引入数量可控的辅助计算点对列表球形译码搜索结果进行补充和更新，提高检测器的收敛性，保证在计算复杂度显著降低的同时，获得与传统MPA检测相同的检测精度。

Description

基于列表球形译码的OTFS—SCMA系统低复杂度信号检测方法 技术领域
本发明属于通信技术领域，特别涉及一种应用于OTFS—SCMA系统的低复杂度信号检测方法。
背景技术
OTFS(Orthogonal Time Frequency Space，正交时间频率空间)是近年来研究较多的基于时延-多普勒域的通信方式。其将时变的多径信道转化成时不变的二维时延-多普勒信道，同时在时延-多普勒域承载信息，从而使一个OTFS帧中的所有符号获得相对恒定的信道增益。研究表明，OTFS在高速运动场景下(如高铁等)误码率性能明显优于传统的OFDM(Orthogonal Frequency Division Multiplexing,正交频分复用)技术。
近些年，有学者在基于OTFS系统的NOMA(Non-Orthogonal Multiple Access,非正交多址接入)方案研究中提出了基于SCMA(Sparse Code Multiple Access,稀疏码分多址接入)的OTFS-SCMA方案，其主要思想是利用二维时延-多普勒域平面的格点来装载SCMA的稀疏码字，借助用户与SCMA稀疏码本一一对应的关系，在接收端利用MPA(Message Passing Algorithm，消息传递算法)完成多用户检测，进而提高OTFS系统的用户连接数。
经典的MPA检测器，其基本原理是将若干个观测符号y与发射符号x分别抽象为观测节点和变量节点，根据等效输入-输出关系将观测节点与变量节点以边相连，从而绘制相应的因子图，在因子图上利用和积算法(Sum Product Algorithm,SPA)来计算传递的消息，经过预设次数的迭代后完成逐符号的检测。为了方便硬件实现，消息的计算与传递一般映射至对数域进行。
由观测节点传递给变量节点的消息可以表示为：
其中，表示与观测符号y相连的第一个发射符号，max*(ab)≈max(a，b),v～{v1}表示除第一个变量节点v1以外与观测节点g相连的其他变量节点， N0表示噪声功率，表示相应的信道状态信息。
由变量节点传递给观测节点的消息可以表示为：
其中，表示对数域上的先验概率。
经过Iter次迭代后，待检测符号的后验概率可以表示为：
通过(3)进一步可求得对数似然比，从而恢复相应的比特信息。
尽管在上行的OTFS-SCMA系统中应用MPA检测器可以确保较好的多用户检测性能，但随着场景中时变的多径信道的多径数增加，更加复杂化的实际信道会使得MPA检测器的计算复杂度呈指数增加，无法控制的复杂度使得以致经典MPA检测器在OTFS-SCMA系统接收端的应用变得困难。
有鉴于此，有学者在基于OFDM的SCMA系统中提出引入LSD技术，减少MPA检测器中(1)部分的计算量，其基本原理是利用多维星座调制技术设计低数量投影的SCMA码本，将等效多维星座矢量作为稀疏码字的代替引入OFDM-SCMA收发系统，利用球形译码技术中的超球面半径C将(1)中全遍历的(为SCMA码本大小，dv为因子矩阵的行重)个待计算点精简为超球内的T个待计算点，从而降低MPA检测器整体的计算复杂度。
对于传统OFDM-SCMA系统，改进后的LSD-MPA检测器在显著降低计算复杂度的同时能够确保较好的误码率性能。但OTFS-SCMA系统用于MPA检测的因子矩阵不同于OFDM-SCMA，前者是由场景中实际的上行多用户等效信道的信道状态信息提取而得，后者则是由SCMA码本设计方案获得。显然，OTFS-SCMA的因子矩阵更加复杂，dv的取值有可能远大于良好设计的SCMA码本所对应的因子矩阵。当传统MPA遍历计算的点数相比引入球形译码精简后的点数T相差超过数十倍时，LSD-MPA带来的复杂度降低更加明显。但同时，消息传递过程中过多必要的消息缺失会造成MPA检测器的迭代发散，从而显著地造成性能损失。
发明内容
本公开提供一种基于列表球形译码算法的时延-多普勒域稀疏码分多址接入系统低复杂度检测方法，其能够实现在显著降低传统MPA复杂度的同时，确保基本一致的误码率性能。
本公开提供的基于列表球形译码算法的OTFS-SCMA系统低复杂度检测方法，主要包括以下步骤：
步骤1，在上行OTFS-SCMA系统，应用基于LSD的MPA检测方法，即：利用列表球形译码算法进行搜索，分别获得对各个观测符号的精简计算点候选集。从而显著降低现有系统多用户检测的计算复杂度。
进一步的，具体方法如下：
考虑J个用户同时接入上行OTFS系统，每个用户分配码字长为K的SCMA稀疏码本，码本大小为
将用户需要传输的信息比特b以正交幅度调制(Quadrature Amplitude Modulation,QAM)的映射规则等效映射为星座矢量u，确定用户的稀疏码字x与星座矢量u的对应关系，通过求逆得到码本与星座矢量之间的映射矩阵G；
对应原上行OTFS-SCMA系统中对稀疏码字x的0行删除及对时延-多普勒域等效信道矩阵H相应的0列删除，将G相应的行和列删除，压缩后代入等效输入输出关系中求得新的等效信道矩阵HG，进而得到接收端观测矢量y与发射端星座矢量u的等效输入输出关系，而后抽象出相应的因子矩阵，确定每一个观测符号yg与星座矢量u的连接关系，得到对应的星座矢量组合ug；
再将等效信道矩阵HG分解为多个行向量HGg,再将HGg扩展并QR分解，得到上三角矩阵R和酉矩阵Q1后将它们代入传统列表球形译码算法中，以后向递归的方式逐符号地完成所有满足条件的星座矢量组合ug的搜索和更新，得到对观测符号yg的精简计算点候选集
步骤2，基于辅助计算点，对基于LSD的MPA检测方法进行补充，即从LSD计算过的点中补充选取辅助计算点，加入所述候选集，以补足所述候选集中缺少的必要码字信息。
直接应用LSD算法设置一个较小的T值(T为计算点候选集的大小)虽然能够显著降低复杂度，但这种精简会造成MPA检测器的消息迭代不收敛，这个问题主要是由于LSD是按逐符号进行搜索和精简，最终确定T个与观测符号距离yg最近的 点，而并未考虑到下一个观测符号yf所需计算的T个点可能需要yg上确定的T个点以外的点的信息，这是MPA检测器在因子图上进行消息迭代的基本规则所需要的。由此带来的必要信息的缺失体现在对数域上即为相应缺失消息的取值为-∞，随着消息通过因子图的边传递并迭代更新于各个节点上，原本各消息的正确取值都会逐渐被-∞替代，从而导致检测算法发散，无法正确地计算出符号的对数似然比。
针对这一问题，本公开利用LSD过程中搜索过的点以及计算过的相应距离选择并添加少量的辅助计算点，在将对LSD-MPA复杂度的影响控制在可忽略的前提下，尽可能地保证检测结果的准确性。
进一步的，具体方法如下：
在完成LSD在某一个观测符号yg上的全部搜索和精简后，利用稀疏码字和星座矢量的一一对应关系对候选集的码字信息全面性进行判断，确认集合内的星座矢量组合ug是否最低程度地包含其对应用户符号的码本的全部信息(每种码字至少包含1次)：
如果已包含每个用户符号的码本中全部种稀疏码字，则无需添加辅助计算点；
如果缺少某些必要码字信息(某几个用户符号的某几种码字)，则将至多个包含这些信息的星座矢量组合ug找出并加入中作为辅助计算点；
更进一步的，具体方法包括：
从LSD计算过的T个点以外的点中，通过组合候选、排列选择，选取距离观测符号yg最近的、包含必要码字信息的一个或几个点作为辅助计算点添加进候选集
步骤3，完成对所有观测符号的列表球形译码搜索和补充辅助计算点后，将得到的计算点候选集送入MPA检测器进行检测。
可见，本公开通过在OTFS-SCMA上行系统引入列表球形译码算法，降低传统MPA检测的计算复杂度；通过引入数量可控的辅助计算点对列表球形译码搜索结果进行补充和更新，提高检测器的收敛性，保证在计算复杂度显著降低的同时，获得与传统MPA检测相同的检测精度，由此构建了基于LSD的完善的OTFS-SCMA系统低复杂度检测方法。目前，现有技术中尚无基于OTFS-SCMA系统的低复杂度MPA检测器以及基于辅助计算点的LSD-MPA检测器设计方法。与现有技术相比，本公开的有益效果是：(1)显著降低了OTFS-SCMA系统中传统MPA检测的计算复杂度；(2)通过对 搜索结果的补充和更新，保证复杂度显著降低的同时，获得与传统MPA检测相同的检测精度，实现了更加合理的复杂度和检测性能的折衷。
附图说明
通过结合附图对本公开示例性实施例进行更详细的描述，本公开的上述以及其它目的、特征和优势将变得更加明显，其中，在本公开示例性实施例方式中，相同的参考标号通常代表相同部件。
图1为上行OTFS-SCMA系统整体框图；
图2为根据本公开的低复杂度检测方法流程图；
图3添加辅助计算点的更新方法示意图；
图4为根据本公开的低复杂度检测器与传统MPA检测器的检测性能比较；
图5为根据本公开的低复杂度检测器与传统MPA检测器的计算复杂度性能比较。
具体实施方式
下面将参照附图更详细地描述本公开的优选实施例。虽然附图中显示了本公开的优选实施例，然而应该理解，可以以各种形式实现本公开而不应被这里阐述的实施例所限制。相反，提供这些实施例是为了使本公开更加透彻和完整，并且能够将本公开的范围完整地传达给本领域的技术人员。
本公开提供了一种应用于时延-多普勒域的稀疏码分多址接入系统的低复杂度检测方法，其主要发明思路是：通过将列表球形译码算法引入上行OTFS-SCMA系统的经典MPA检测器中，减少MPA检测器中由观测节点传递给变量节点这部分消息的计算量，降低整体系统的计算复杂度；通过对列表球形译码算法搜索获得的候选计算点集合理选取并添加辅助计算点，提高检测器的收敛性，实现检测性能和复杂度的合理折衷，进一步提高传输性能。
结合具体实施例和附图，对本公开做进一步详细描述如下。
附图1展示了示例性的采用低复杂度检测器的上行OTFS-SCMA系统整体结构。设系统子载波数为M，子载波间隔为Δf；符号个数为N，符号持续时间为Ts；接入用户数为J；第j个用户的上行时延-多普勒信道包含的多径数为Pj。
本公开所述的一种低复杂度检测方法，主要包括以下步骤:
步骤1，在上行OTFS-SCMA系统，应用基于LSD的MPA检测方法，即：利用列表球形译码算法进行搜索，分别获得对各个观测符号的精简计算点候选集；具体方法如下：
考虑J个用户同时接入上行OTFS系统，每个用户分配码字长为K的SCMA稀疏码本，码本大小为
将用户需要传输的信息比特b以正交幅度调制(Quadrature Amplitude Modulation,QAM)的映射规则等效映射为星座矢量u，确定用户的稀疏码字x与星座矢量u的对应关系，通过求逆得到码本与星座矢量之间的映射矩阵G；
对应原上行OTFS-SCMA系统中对稀疏码字x的0行删除及对时延-多普勒域等效信道矩阵H相应的0列删除，将G相应的行和列删除，压缩后代入等效输入输出关系中求得新的等效信道矩阵HG，进而得到接收端观测矢量y与发射端星座矢量u的等效输入输出关系，而后抽象出相应的因子矩阵，确定每一个观测符号yg与星座矢量u的连接关系，得到对应的星座矢量组合ug；
再将等效信道矩阵HG分解为多个行向量HGg,再将HGg扩展并QR分解，得到上三角矩阵R和酉矩阵Q1后将它们代入传统列表球形译码算法中，以后向递归的方式逐符号地完成所有满足条件的星座矢量组合ug的搜索和更新，得到对观测符号yg的精简计算点候选集
步骤2，基于辅助计算点，对基于LSD的MPA检测方法进行补充，即从LSD计算过的点中补充选取辅助计算点，加入所述候选集，以补足所述候选集中缺少的必要码字信息；具体方法如下：
在完成LSD在某一个观测符号yg上的全部搜索和精简后，利用稀疏码字和星座矢量的一一对应关系对候选集的码字信息全面性进行判断，确认集合内的星座矢量组合ug是否最低程度地包含其对应用户符号的码本的全部信息(每种码字至少包含1次)：
如果已包含每个用户符号的码本中全部种稀疏码字，则无需添加辅助计算点；
如果缺少某些必要码字信息(某几个用户符号的某几种码字)，则将至多个包含这些信息的星座矢量组合ug找出并加入中作为辅助计算点；
更进一步的，具体方法包括：
从LSD计算过的T个点以外的点中，通过组合候选、排列选择，选取距离观测符号yg最近的、包含必要码字信息的一个或几个点作为辅助计算点添加进候选集
步骤3，完成对所有观测符号的列表球形译码搜索和补充辅助计算点后，将得到的计算点候选集送入MPA检测器进行检测。
如附图2所示，本公开所述的一种低复杂度检测方法，主要包括以下步骤：
步骤1：利用列表球形译码算法，得到精简的计算点候选集：
首先，在接收端确认时延-多普勒域观测符号yg与其相连的多个用户符号组成的星座矢量组合ug(矢量长度为L)之间的等效输入输出关系，抽象出因子矩阵F(行重为dv)，得到等效信道矢量HGg；再将观测符号yg和等效信道矢量HGg分别扩展为长度为(L+1)的列向量和列满秩矩阵，其中α＞0，IL为L阶单位阵；然后将进行QR分解：
将(L+1)×L维酉矩阵Q1和上三角矩阵R输入传统列表球形译码算法：
将列表球形译码算法的超球面半径C设置为+∞，以后向递归的方式从第L层开始搜索星座矢量组合ug中的每一个元素直至第1层，计算它们与观测符号yg的欧氏距离以用来实时更新半径C的取值，最后记录下距离最近的T个星座矢量组合，作为等待送入MPA检测器进行(1)计算的候选点集同时记录整个搜索过程中所有搜索过的点对应的欧氏距离d(ug)(若未搜索至第1层，则记录部分欧氏距离)。
步骤2：对计算点候选集判断是否需要补充辅助计算点：
在完成LSD在某一个观测符号yg上的全部搜索和精简后，利用用户发射比特、星座矢量以及稀疏码字之间的一一对应关系，对集合中ug包含的dv个用户符号的码字信息全面性进行判断：
1)若T个星座矢量组合已包含每个用户符号的全部种稀疏码字(每种码字至少包含1次)，则计算点候选集无需进行额外操作；
2)若T个星座矢量组合中缺少某几个用户符号的某几种码字，则需要为添加 某一个或某几个星座矢量组合作为辅助计算点，以补全必要的码字信息，避免MPA检测器出现迭代发散的可能，其中表示辅助计算点的个数，最大个数为个。
关于辅助计算点的判断和计算，可以是在每完成对一个观测符号的LSD搜索和精简后即进行，也可以在完成对所有观测符号的搜索和精简后再进行。
步骤3：组合候选，即根据步骤2对的判断，构建待增加的辅助计算点组合：
对将每一个用户符号缺少的码字种类进行排列组合，组成待提取辅助计算点的集合举例来说：
假设dv＝3，T＝4，其中表示这个星座矢量组合是由与yg相连的3个用户分别发送他们的第1种码字(即输入比特为(00)、星座矢量为(+1，+1))组合而成，这里以进制整数{1}代表码字的序数。可以看出，候选集缺少用户1发送第3、4种码字的信息，缺少用户2发送第4种码字的信息，而用户3的四种码字信息是全面包含的。将缺少的信息进行组合，不缺少的部分就以全集进行列举，可以得到待提取的辅助计算点集合：
步骤4：排列选择：
优选通过LSD已经搜索并记录的相应结果，得到中大部分点距离实际观测符号yg的欧氏距离，少部分未计算的在这一步中进行补充计算并记录。然后，为了尽量保证检测的准确性，采用复杂度较低的归并排序法将中所有的星座矢量组合按欧氏距离从大到小排序，挑选距离最近的一个点首先添加到中，并删除中所有包含相应码字的组合(若只剩1种则不删除)。
附图3展示了本公开中添加辅助计算点以更新候选点集的方法示意图。同上举例来说，假设(3，4，1)是中距离近的点，则更新后的此时，用户2和用户3已经包含全部必要信息，用户1尚缺少第4种码字的信息，因此再对重复做排序并提取最小距离的点加入即可。假设星座矢量组合(4，4，2)是集合剩下所有点中距离最小的，则最终更新的最后两个添入的星座矢量组合 即为辅助计算点。由此确保包含全面的码字信息。
步骤5：完成所有观测符号的列表球形译码、检查并添加必要的辅助计算点后，将更新后的计算点候选集代入传统MPA检测器进行消息迭代更新。在经过设置的最大迭代次数Iter或算法已收敛后，通过(3)输出所有用户发送符号的后验概率并计算LLR，最终完成比特信息的恢复。
本实施例中，将前述实施例中步骤二“基于辅助计算点，对基于LSD的MPA检测方法进行补充，即从LSD计算过的点中补充选取辅助计算点，加入所述候选集，以补足所述候选集中缺少的必要码字信息”描述为：步骤二、步骤三、步骤四，加以阐述。
由图4的仿真结果可以看出，本公开提出的基于辅助计算点的低复杂度检测器在T值设置为400，减少传统MPA检测器计算的全遍历点数的约90％时，仍能确保与其基本一致的误码率性能。同时，也显示出当总点数与精简计算的点数差距过大时，仅利用LSD降低复杂度而不检查必要信息的缺失会导致显著的误码率性能损失，而仅添加至多个辅助计算点则可以显著避免这个问题。
由图5的仿真结果可以看出，本公开提出的基于辅助计算点的低复杂度检测器相比传统的MPA检测器复杂度显著降低，在信道包含的多径数增加变得更加复杂和实际时，例如多径数P的取值由2增加到3，提出的检测器在T值与全遍历点数的比值为2000/65536≈3％、检测性能在高信噪比时基本一致的前提下，仍能确保整体的计算复杂度降低75％以上。
通过以上实施例可以看出，本公开通过将列表球形译码技术引入OTFS-SCMA系统，减少传统MPA检测器计算观测节点传递给变量节点的消息计算量，从而显著降低了系统整体的检测复杂度，使得性能良好的MPA检测器的应用更为实际；进一步地，若直接在计算量削减较大的情况下使用，则可能出现由必要码字信息缺失带来的检测器迭代发散问题，会导致检测性能损失较大，而通过有策略地搜索并添加少量辅助计算点，将能够保证在复杂度明显降低的同时仍可将检测性能的损失抑制在可以忽略的水平，实现检测性能和复杂度的合理折衷，提高传输性能。
上述技术方案只是本发明的示例性实施例，对于本领域内的技术人员而言，在本发明公开了应用方法和原理的基础上，很容易做出各种类型的改进或变形，而不仅限 于本发明上述具体实施例所描述的方法，因此前面描述的方式只是优选的，而并不具有限制性的意义。
工业实用性
本发明一种应用于OTFS-SCMA系统的低复杂度检测方法，在OTFS-SCMA上行系统引入列表球形译码算法，降低传统MPA检测的计算复杂度；引入数量可控的辅助计算点对列表球形译码搜索结果进行补充和更新，提高检测器的收敛性，保证在计算复杂度显著降低的同时，获得与传统MPA检测相同的检测精度。本发明具有良好的工业实用性。

Claims (6)

  1. 一种基于列表球形译码的OTFS-SCMA系统低复杂度信号检测方法，包括以下步骤：
    在上行OTFS-SCMA系统，利用列表球形译码算法进行搜索，获得对某一观测符号的精简计算点候选集；
    对缺少必要码字信息的计算点候选集补充辅助计算点，以补足所包含的码字信息；
    完成对所有观测符号的列表球形译码搜索和补充辅助计算点后，将得到的计算点候选集送入MPA检测器进行检测。
  2. 根据权利要求1所述的低复杂度信号检测方法，其特征在于，所述利用列表球形译码算法进行搜索，获得对某一观测符号的精简计算点候选集的步骤，具体包括：
    将用户需要传输的信息比特b以正交幅度调制的映射规则映射为星座矢量u，确定稀疏码字x和星座矢量u的一一对应关系，通过求逆的方式计算出稀疏码本与星座矢量的映射矩阵G；
    以压缩上行OTFS-SCMA系统中稀疏码字和等效信道矩阵的方式将G相应的行和列删除，推导出接收端观测矢量y与发射端星座矢量u的等效输入输出关系，抽象出相应的因子矩阵，确定每一个观测符号与星座矢量u的连接关系，得到对应的星座矢量组合；
    将等效信道矩阵HG的第g行分量HGg扩展并进行QR分解，得到上三角矩阵R和酉矩阵Q1，代入传统列表球形译码算法，进行后向递归搜索，得到与观测符号yg距离最近的T个星座矢量组合ug，即为对观测符号yg的精简计算点候选集
  3. 根据权利要求1或2所述的低复杂度信号检测方法，其特征在于，所述对缺少必要码字信息的计算点候选集补充辅助计算点的步骤，具体包括：
    在完成LSD在某一观测符号上的全部搜索和精简后，利用稀疏码字和星座矢量的一一对应关系对的码字信息全面性进行判断和处理：
    如果已包含每个用户符号的码本中全部种稀疏码字，则无需添加辅助计算点；
    如果缺少某些必要码字信息，则找出至多个包含这些信息的星座矢量组合作为辅助计算点，加入中。
  4. 根据权利要求3所述的低复杂度信号检测方法，其特征在于，所述找出至多个包含这些信息的星座矢量组合作为辅助计算点，加入中的步骤，具体包括：
    组合候选：将当前候选集待补充的必要信息组合以ug的形式列举作为候选辅助计算点，将所有待添加以更新的辅助计算点整合为一个新的候选集
    排列选择：将中与观测符号yg距离最小的一个点作为第一个辅助计算点添加进中；
    重复所述组合候选和排列选择的步骤，直至确保将距离观测符号yg最近的个星座矢量组合ug确认为辅助计算点，的取值范围为更新后信息完整的计算点候选集
  5. 根据权利要求4所述的低复杂度信号检测方法，其特征在于，所述排列选择的步骤，具体方法包括：
    利用列表球形译码已搜索并计算过的大部分点及其距离值，补充计算少量未搜索至最后一层的点的半径，利用复杂度较低的归并排序法快速找到第一个辅助计算点。
  6. 根据权利要求1或5所述的低复杂度信号检测方法，其特征在于，所述对缺少必要码字信息的计算点候选集补充辅助计算点的步骤，具体包括：
    对计算点候选集判断是否需要补充辅助计算点；
    组合候选：根据对的判断，构建待增加的辅助计算点组合，对将每一个用户符号缺少的码字种类进行排列组合，组成待提取辅助计算点的集合
    排列选择：采用复杂度较低的归并排序法将中所有的星座矢量组合按欧氏距离从大到小排序，挑选距离最近的一个点首先添加到中。
PCT/CN2023/106807 2022-06-01 2023-07-11 基于列表球形译码的otfs—scma系统低复杂度信号检测方法 WO2024078068A1 (zh)

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