Article(id=1251893511113617992, tenantId=1146029695717560320, journalId=1251234473337991274, issueId=1251893504037831074, articleNumber=null, orderNo=null, doi=10.3969/j.issn.1003-3114.2025.05.020, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1733673600000, receivedDateStr=2024-12-09, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1776404272105, onlineDateStr=2026-04-17, pubDate=1758124800000, pubDateStr=2025-09-18, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1776404272105, onlineIssueDateStr=2026-04-17, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1776404272105, creator=13701087609, updateTime=1776404272105, updator=13701087609, issue=Issue{id=1251893504037831074, tenantId=1146029695717560320, journalId=1251234473337991274, year='2025', volume='51', issue='5', pageStart='877', pageEnd='1134', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=null, createTime=1776404270419, creator=13701087609, updateTime=1776404832543, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1251895861849043019, tenantId=1146029695717560320, journalId=1251234473337991274, issueId=1251893504037831074, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1251895861849043020, tenantId=1146029695717560320, journalId=1251234473337991274, issueId=1251893504037831074, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=1073, endPage=1079, ext={EN=ArticleExt(id=1251893513651172004, articleId=1251893511113617992, tenantId=1146029695717560320, journalId=1251234473337991274, language=EN, title=Joint Decoding Method for Two-user Polar Coded Generalized Spatial Modulation System, columnId=1251893508886446519, journalTitle=Radio Communications Technology, columnName=Special Topic:Frontiers in Intelligent Communication, Storage, and Information Processing Technologies, runingTitle=null, highlight=null, articleAbstract=

Multiple Input Multiple Output (MIMO) technology significantly enhances signal transmission rates and system reliability through multi-antenna systems. To improve spectral efficiency and anti-interference capabilities, spatial modulation technology, as an extension of MIMO, has been proposed and widely applied. Generalized Spatial Modulation (GSM) further integrates multiple modulation schemes, enhancing the system's performance. Polar codes, as an efficient error correction code, leverage channel polarization to transform physical channels into virtual channels with varying levels of reliability, thus effectively improving the performance of MIMO and spatial modulation systems. This paper presents a decoding scheme for multi-user polar codes, aimed at optimizing the decoding process in the uplink Polar Coded-Generalized Spatial Modulation (PC-GSM) system. By combining the channel polarization characteristics of polar codes with the advantages of GSM, the scheme improves decoding algorithms, enhancing the reliability and data transmission rate of multi-user systems. Simulation results show that the proposed decoding scheme significantly boosts system performance, providing a novel solution for the integration of multi-user polar codes and spatial modulation technology.

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多输入多输出(Multiple Input Multiple Output,MIMO)技术通过多天线系统显著提升信号传输速率和系统可靠性。为提高频谱效率和抗干扰能力,空间调制技术作为MIMO的扩展被提出并得到广泛应用。广义空间调制(Generalized Spatial Modulation,GSM)进一步结合多种调制方式,提升系统性能。极化码作为高效的纠错码,通过信道极化将物理信道转化为具有不同可靠性的虚拟信道,有效提高MIMO和空间调制系统的性能。提出一种联合多用户的极化码译码方案,旨在优化在上行极化码广义空间调制(Polar Coded-GSM,PC-GSM)系统中的译码过程。该方案结合了极化码的信道极化特性和GSM的优势,通过改进译码算法,提升了多用户系统的可靠性和数据传输速率。仿真结果表明,所提出的联合译码方案能够显著提高系统性能,为极化码与多用户空间调制系统的结合提供新的解决思路。

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王远平 男,(1999—),硕士研究生。主要研究方向:极化码、空间调制。

杜伟庆 男,(1985—),硕士,助理研究员。主要研究方向:视频编码、数字电视、无线通信。

谢肇鹏 男,(1995—),博士,讲师,硕士生导师。主要研究方向:空间调制、物理层网络编码、极化码。

陈平平 男,(1986—),博士,教授,博士生导师。主要研究方向:LDPC码、物理层网络编码、极化码。

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王远平 男,(1999—),硕士研究生。主要研究方向:极化码、空间调制。

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王远平 男,(1999—),硕士研究生。主要研究方向:极化码、空间调制。

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杜伟庆 男,(1985—),硕士,助理研究员。主要研究方向:视频编码、数字电视、无线通信。

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杜伟庆 男,(1985—),硕士,助理研究员。主要研究方向:视频编码、数字电视、无线通信。

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谢肇鹏 男,(1995—),博士,讲师,硕士生导师。主要研究方向:空间调制、物理层网络编码、极化码。

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谢肇鹏 男,(1995—),博士,讲师,硕士生导师。主要研究方向:空间调制、物理层网络编码、极化码。

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陈平平 男,(1986—),博士,教授,博士生导师。主要研究方向:LDPC码、物理层网络编码、极化码。

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陈平平 男,(1986—),博士,教授,博士生导师。主要研究方向:LDPC码、物理层网络编码、极化码。

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Simulation Parameters

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参数
单用户发射天线数量Nt4
基站接收天线数量Nr8
用户数L2
单用户码字长度(p+qV/bit64,128
路径损耗Π1Π2(8.5,0.6)
SCL译码路径数4
调制方式正交相移键控
), ArticleFig(id=1251895526157926844, tenantId=1146029695717560320, journalId=1251234473337991274, articleId=1251893511113617992, language=CN, label=表1, caption=

仿真参数

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参数
单用户发射天线数量Nt4
基站接收天线数量Nr8
用户数L2
单用户码字长度(p+qV/bit64,128
路径损耗Π1Π2(8.5,0.6)
SCL译码路径数4
调制方式正交相移键控
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两用户极化码广义空间调制系统的联合译码方法
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王远平 1 , 杜伟庆 1 , 谢肇鹏 2 , 陈平平 1
无线电通信技术 | 专题:智能通信、存储与信息处理技术前沿 2025,51(5): 1073-1079
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无线电通信技术 | 专题:智能通信、存储与信息处理技术前沿 2025, 51(5): 1073-1079
两用户极化码广义空间调制系统的联合译码方法
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王远平1, 杜伟庆1, 谢肇鹏2, 陈平平1
作者信息
  • 1.福州大学 物理与信息工程学院,福建 福州 350116
  • 2.福州大学 先进制造学院,福建 泉州 362251
  • 王远平 男,(1999—),硕士研究生。主要研究方向:极化码、空间调制。

    杜伟庆 男,(1985—),硕士,助理研究员。主要研究方向:视频编码、数字电视、无线通信。

    谢肇鹏 男,(1995—),博士,讲师,硕士生导师。主要研究方向:空间调制、物理层网络编码、极化码。

    陈平平 男,(1986—),博士,教授,博士生导师。主要研究方向:LDPC码、物理层网络编码、极化码。

Joint Decoding Method for Two-user Polar Coded Generalized Spatial Modulation System
Yuanping WANG1, Weiqing DU1, Zhaopeng XIE2, Pingping CHEN1
Affiliations
  • 1.School of Physics and Information Engineering, Fuzhou University, Fuzhou 350116, China
  • 2.School of Advanced Manufacturing, Fuzhou University, Quanzhou 362251, China
出版时间: 2025-09-18 doi: 10.3969/j.issn.1003-3114.2025.05.020
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多输入多输出(Multiple Input Multiple Output,MIMO)技术通过多天线系统显著提升信号传输速率和系统可靠性。为提高频谱效率和抗干扰能力,空间调制技术作为MIMO的扩展被提出并得到广泛应用。广义空间调制(Generalized Spatial Modulation,GSM)进一步结合多种调制方式,提升系统性能。极化码作为高效的纠错码,通过信道极化将物理信道转化为具有不同可靠性的虚拟信道,有效提高MIMO和空间调制系统的性能。提出一种联合多用户的极化码译码方案,旨在优化在上行极化码广义空间调制(Polar Coded-GSM,PC-GSM)系统中的译码过程。该方案结合了极化码的信道极化特性和GSM的优势,通过改进译码算法,提升了多用户系统的可靠性和数据传输速率。仿真结果表明,所提出的联合译码方案能够显著提高系统性能,为极化码与多用户空间调制系统的结合提供新的解决思路。

空间调制  /  极化码  /  信道极化  /  多输入多输出

Multiple Input Multiple Output (MIMO) technology significantly enhances signal transmission rates and system reliability through multi-antenna systems. To improve spectral efficiency and anti-interference capabilities, spatial modulation technology, as an extension of MIMO, has been proposed and widely applied. Generalized Spatial Modulation (GSM) further integrates multiple modulation schemes, enhancing the system's performance. Polar codes, as an efficient error correction code, leverage channel polarization to transform physical channels into virtual channels with varying levels of reliability, thus effectively improving the performance of MIMO and spatial modulation systems. This paper presents a decoding scheme for multi-user polar codes, aimed at optimizing the decoding process in the uplink Polar Coded-Generalized Spatial Modulation (PC-GSM) system. By combining the channel polarization characteristics of polar codes with the advantages of GSM, the scheme improves decoding algorithms, enhancing the reliability and data transmission rate of multi-user systems. Simulation results show that the proposed decoding scheme significantly boosts system performance, providing a novel solution for the integration of multi-user polar codes and spatial modulation technology.

spatial modulation  /  polar coded  /  channel polarization  /  MIMO
王远平, 杜伟庆, 谢肇鹏, 陈平平. 两用户极化码广义空间调制系统的联合译码方法. 无线电通信技术, 2025 , 51 (5) : 1073 -1079 . DOI: 10.3969/j.issn.1003-3114.2025.05.020
Yuanping WANG, Weiqing DU, Zhaopeng XIE, Pingping CHEN. Joint Decoding Method for Two-user Polar Coded Generalized Spatial Modulation System[J]. Radio Communications Technology, 2025 , 51 (5) : 1073 -1079 . DOI: 10.3969/j.issn.1003-3114.2025.05.020
MIMO技术作为现代通信系统的核心,利用多天线系统显著提升了信号传输速率和系统可靠性[1]。然而,随着通信需求的不断增长,如何在有限的频谱资源下进一步提高系统性能已成为研究的关键问题。为了提升通信效率,空间调制作为MIMO技术的扩展形式被提出。与传统MIMO系统不同,空间调制将发送天线的数量作为额外的信息源,并且在每个发送时隙只激活一个天线[2]。这种方法有效消除了信道间干扰,大大简化了接收机的设计,同时提升了系统性能。GSM在空间调制的基础上进一步扩展,通过结合多种调制方式和信号映射策略,进一步提高了系统的频谱效率和抗干扰能力[3]。随着未来移动数据流量需求的不断增加,空间调制技术亟需从单用户点对点传输扩展到多用户配置。多用户GSM系统通过支持多个用户共享相同的频率和时间资源,并引入GSM的优化技术,显著提升了系统容量和抗干扰能力,从而有效应对了日益增长的通信需求。
为了提高MIMO系统的可靠性,通常采用Turbo码[4]、低密度奇偶校验码[5]和极化码[6]等纠错码对信号进行编码,从而有效提升系统性能。其中,极化码由Arikan提出,并被证明能够达到二进制离散无记忆信道的信道容量。极化码通过将物理信道转化为一组虚拟的子信道来实现,这些子信道具有非常高或非常低的可靠性。该过程依赖于高效的编码、译码以及构造算法的支持。为了进一步提升极化码的性能,研究者提出了多种译码方法,包括串行消除(Successive Cancellation,SC)译码[7]、串行消除列表(Successive Cancellation List,SCL)译码[8]和基于循环冗余校验的SCL译码等[9]
目前,极化码与MIMO系统以及空间调制技术的结合,成为提升无线通信系统性能的一个重要研究方向。研究表明,将极化码与MIMO技术结合,可以有效利用多个发送天线的优势,增强系统的可靠性和数据传输速率。通过这种结合,极化码的纠错能力在多天线系统中得到了充分发挥,进而提高了系统的整体性能。研究者们在该领域的工作集中在设计更高效的编码方案、优化译码算法以及在实际通信场景中的性能优化。例如,Dai等[10]提出一种结合极化码和MIMO技术的框架,即极化码MIMO系统,通过信道极化有效提升了系统性能。Chen等[11]提出了一种极化码与GSM的联合设计,相较于传统的极化码空间调制方案,在系统性能上表现更佳。此外,针对多用户环境下的优化问题,Feng等[12]提出了一种广义极化预编码方案,用于提升上行多用户MIMO系统的可靠性和容量。
尽管极化码与MIMO或GSM结合的系统设计在提升通信性能方面取得了显著进展,但在实际应用中仍存在一些挑战和不足,尤其是在多用户场景下以及译码复杂度方面。传统的设计方法主要集中在单用户系统中,但随着多用户通信需求的增加,如何在共享相同频率和时间资源的情况下保证每个用户译码性能,成为了一个尚未解决的关键问题。
目前,关于上行多用户的PC-GSM系统译码研究较少。本文立足于上行空间调制系统,研究该场景下的两用户极化码译码,主要工作如下:
①介绍了两用户PC-GSM系统的模型,并阐述了极化码的信道极化基本原理以及编码过程。
②详细介绍了极化码嵌套结构的基本原理及其计算步骤。基于此提出了一种多用户联合的极化码译码方案,旨在优化上行PC-GSM系统中的译码过程。
③仿真表明,所提出的方案能够有效提升上行PC-GSM系统的译码性能。
图1展示了基于联合译码方案的两用户PCGSM系统。表示用户l的一个N维向量{al,1al,2,…,al,N},H表示矩阵。系统中共有2个用户,每个用户配备Nt根发射天线,基站则配备Nr根接收天线,用于接收所有用户的叠加信号,发射端采用GSM。
在每次传输中,每个用户从Nt根发射天线中选择Na根激活天线,用于传输数据。天线激活的选择能够携带的信息。例如,若Nt=4且Na=2,则可能的激活天线索引有{(1,2),(1,3),(1,4),(2,3)}。设dl为激活天线索引生成的天线激活向量,计算为:
式中:l∈{AB},dl,i=1表示l的第i根天线被激活,dl,i=0表示未激活,向量中有且仅有Na个元素为1。此外,额外的q=lb(M)bit被映射为一个M阶正交振幅调制符号sl。因此,在每次信道使用中,每个用户传输比特数为p+q=+lb(M)。信源信息首先通过极化码编码器进行编码,然后通过GSM映射,并在V个时隙内传输到接收端。
对于第l个用户,每个用户发送独立的信源信息。这些信源信息经过极化码编码器,生成对应的码字。随后,码字被映射到GSM符号BlLNt×V的矩阵),Bl的每一列为天线发送向量,定义为blv),v=1,2,…,V。具体来说,码字比特被划分为2个部分:①每q bit用于调制符号的映射;②每p bit决定符号的发射天线位置。对于给定的天线激活向量dl和调制符号sl,发送信号向量计算为:
所有用户的发送信号向量通过无线信道同时传输到基站端,对于第v个时隙,接收到的yv)可表示为:
式中:yv)为Nr×1的接收向量,Hll与基站之间的信道系数。假设用户与基站之间的距离不同,则第l个用户与基站之间的信道表示为:
式中:Πl>0表示第l个用户与基站之间的路径损耗。复信道H的元素服从独立同分布的复高斯分布,其均值为0,方差为1。噪声向量n表示接收端的加性噪声,其是均值为0,方差为σ2的复高斯随机变量。
接收端通过GSM检测对yv)进行检测,以恢复多用户的联合传输符号。随后,联合译码器利用多用户联合译码算法同时对用户AB进行译码,最终通过用户分离模块获得各用户的原始信息比特。该系统的设计目标是通过联合译码器方案优化PCGSM的性能,提升多用户场景下的传输可靠性。
一个二进制输入离散无记忆信道由W:XY表示,其中输入字母表为X={0,1},输出字母表为Y,信道转移概率定义为{Wy|x):xXyY}。源向量由2组比特构成:uA表示信息比特,表示冻结比特,其中|A|=K。极化码可通过其生成矩阵来进行编码:
式中:生成矩阵GNF2n次克罗内克积构成,其中F2=n=lb(N)为正整数。
在构造长度为N的极化码时,将N个独立副本的给定二进制输入离散元记忆信道W合并并分割成N个子信道i=1,2,…,N。令|ui)表示第i个信道转移概率,其中输入比特为ui,输出为,具体定义为:
子信道的可靠性可以通过编码构造方法进行评估,包括高斯近似[13]、密度演化[14]和蒙特卡罗方法[15]。选择K个最可靠的比特子信道用于传输信息比特,剩余的比特子信道则用于冻结比特,并将其设置为0。
极化码的嵌套结构是一种通过将多个信息序列分别编码后再合并的方式,与直接编码一个长信息序列的效果相同[16]。这种结构的关键是将一个长序列分解成2个子序列,分别进行编码,再通过异或操作将其合并成一个最终的输出序列。这个过程不仅提高了编码的灵活性,还使得极化码在应用中能够提升极化效果。
在极化码的嵌套结构中,考虑2个信息序列uAuB,且uAuB分别代表2个独立的信息流。通过极化编码分别对其进行编码,产生各自的码字:
在此基础上构造长码字x,上半部分由2个子码字的异或结果构成,表示为xAxB,其中⊕表示按位异或操作,而下半部分则直接取子码字xB。因此,长码字的最终构成可表示为:
最终的码字zxAxB经过上述嵌套编码和异或操作得到。同时,x的生成可视为对信息流[uAuB]进行直接编码的结果。直接对[uAuB]进行编码的x可表示为:
因此,嵌套结构采用了先对uAuB分别编码并通过异或操作得到z。从编码的结果来看,该码字与直接对[uAuB]进行编码得到的z完全一致。将上述过程表示为总公式,可得到:
在两用户PC-GSM系统中,每个用户的输入信息流经过独立的极化编码生成相应的码字。GSM将每个用户的码字映射到不同的天线激活模式进行发送。尽管每个用户的编码信息和调制符号是独立的,但接收端可将2个用户的接收符号拼接成一个长码字并进行译码。
在GSM系统中,信号的检测过程是一个关键环节。QR检测作为一种常见的检测方法,在GSM系统中得到了应用,特别是在接收端对信号进行解调和译码时[17]。QR检测算法通常基于QR分解技术,通过对接收到的信号进行矩阵分解,利用其结构特性来简化信号的检测过程。具体来说,QR检测算法的第一步是对复信道H进行QR分解,得到H=QR,其中Q为正交矩阵且QHQ=IR为上三角矩阵;第二步是将接收到的信号y与矩阵QH相乘,得到的输出可表示为:
若将xz分别划分为2个部分,记为xv)=[xAv);xBv)]和zv)=[zAv);zBv)],那么矩阵R的作用可表示为:
这种划分方式与极化码嵌套结构中的码字构造方式存在一定的相似性。QR检测中的等效信号zv)的生成过程可看作是将上半部分信息zAv)与下半部分信息zBv)通过矩阵变换进行关联,类似于极化码嵌套结构中通过编码和异或操作整合信息的过程。因此,可将bAv)和bBv)分别视为子码字,而将zv)视为一个整体的长码字。
在PC-GSM系统中,对数似然比(Logarithmic Likelihood Ratio,LLR)的计算基于每个比特的发送符号集合,这些符号集合通过GSM映射规则得到。对于每个比特xl,i,根据GSM的映射规则,确定其对应的发送符号集合B,该符号集合对于每个比特值分别为xl,i=0和xl,i=1的情况进行计算。考虑到嵌套结构,LLR的计算需要分为2个部分来进行:一部分对应上半部分的异或操作,另一部分对应下半部分的码字。对于上半部分的信息,每个比特xl,i的LLR计算为:
在该系统中,每个时隙传输(p+q)bit,则iv之间满足如下关系:。转移概率可表示为:
式中:BxA,ixB,i=α)={bB|xA,ixB,i=α}从集合B中筛选出满足xA,ixB,i=α条件的所有发送向量b。对于下半部分的码字,LLR的计算可表示为:
转移概率可表示为:
通过将这2个部分LLR进行拼接,得到的综合LLR表示为:
拼接后的LLR将被送入长码的译码器进行译码处理。在译码器中,长码的译码过程将利用这些LLR值作为输入,恢复出原始的比特流,从而获得接收信号对应的估计结果。传统译码方法中,用户A和用户B分别计算各自的LLR,并将其送入各自的译码器进行解码。相比之下,联合译码采用嵌套结构来计算LLR,并将计算得到的LLR合并后输入到一个2倍码长的单一极化码译码器中进行解码。极化码的特性表明,随着码长的增加,极化效应愈加显著。在长码长下,极化码的子信道逐渐趋向于极化,部分子信道容量接近于0,其他子信道容量接近于1。这种极化效应导致信息位能够分配到那些接近于1的子信道上,而更长的码字意味着子信道具有更大的有效信道容量。因此,随着码长的增加,极化效应的增强使得系统能够在更大容量子信道上传输更多信息,提高了误比特率(Bit Error Ratio,BER)性能。
本节分析了提出的联合译码方案在两用户PCGSM系统中的BER性能。采用蒙特卡罗代码构造方法来选择极化码的信息位和冻结位。为了进行对比,将文献[11]中的PC-GSM系统译码结构应用到多用户场景下,作为传统译码方案进行对比。传统译码方案采用用户各自解码和串行干扰消除方法。本文使用的仿真参数如表1所示。
图2展示了PC-GSM系统中联合译码方案和传统方案在不同译码方式下的BER性能对比,其中极化码码长为64。GSM通过在每个时隙激活多个天线来提高效率。在该配置中,每个用户从4个天线中选择2个天线来发送相同的QAM符号,Nt=4且Na=2。因此,系统实现了更高的频谱效率,并在每个时隙传输额外的2 bit。本文考虑了极化码采用SC和SCL两种译码方式的情况。具体来说,在极化码采用SC译码的情况下,使用联合译码方案(Proposed Joint Decoding-SC)多用户PC-GSM系统,在BER=10-4时,相比于使用传统方案(Traditional Decoding-SC)的系统,提出的联合译码方案性能提升约0.5 dB。同样地,在采用SCL译码时,联合译码方案(Proposed Joint Decoding-SCL)也表现出明显优于传统译码方案(Traditional DecodingSCL)的性能。
图3展示了码长为128 bit时的系统BER性能,进一步验证了联合译码方案的有效性。联合译码方案在各信噪比条件下均表现出更低的BER,与传统译码方案相比,实现了约0.36 dB的性能增益。此外,通过对比图2图3的结果可以看出,在采用相同译码方案的情况下,码长更长的系统表现出更低的BER,充分说明了极化码长度对系统性能的影响。此外,联合译码方案不仅适用于SC和SCL译码,还可以有效应用于其他极化码译码方案。通过联合译码能够进一步提升多用户系统中的解码性能。结果表明,无论是在采用SC还是SCL的极化码译码方案下,本文提出的联合译码方案都能有效提升PC-GSM系统的性能。
为了分析译码方案对极化效应的影响,对极化码子信道容量进行了仿真分析。极化效应的强弱可以通过子信道容量的分布特征反映,当子信道容量的值更接近0或1 b/s时,极化效应越显著[18]图4展示了在信噪比为4 dB条件下,传统方案与联合译码方案在PC-GSM系统中的两用户极化码子信道的对称信道容量对比结果。具体而言,传统译码方案为2个用户分别计算64 bit长度的极化码信道容量,而联合译码方案则联合计算一个128 bit长度的信道容量。仿真结果表明,与传统译码方案相比,联合译码方案能够更有效地增强极化效应,导致更多子信道的容量接近0或1。这种极化效应的增强使得信息位能够被分配到容量较大的子信道上,充分利用信道资源,同时减少冻结位的容量损失,进一步提升系统的整体性能。相比之下,传统译码方案未能充分利用极化效应,导致部分子信道的容量未能充分发挥,因此联合译码方案显著优于传统方案,表现出更低的BER。综上所述,本文提出的联合译码方案在多用户PC-GSM系统中的优势得到了充分验证。通过BER仿真曲线和极化码子信道容量分布的分析,联合译码方案展现了显著的性能改进,提高了BER性能,增强了极化效应。此外,该方案具备良好的适用性,能够与不同的极化码译码方法及多种空间调制系统灵活结合,为多用户通信系统的设计和优化提供了有效的技术支持。
本文研究了上行两用户PC-GSM系统中的联合译码方案。介绍了两用户PC-GSM系统模型,并阐述了极化码的信道极化原理及编码过程。详细讨论了极化码的嵌套结构及其计算步骤,提出了一种两用户联合极化码译码方案,旨在优化系统译码性能。通过仿真,比较了传统译码方案与联合译码方案的BER性能。仿真结果表明,联合译码方案相比传统译码方案在多用户场景下具有显著的性能提升。综上,本文提出的联合译码方案为上行PC-GSM系统提供了一种有效的译码策略,能够提高系统的通信可靠性。未来的研究可以探索将该方案扩展到更多用户的场景,进一步提升其在更大规模系统中的性能。随着用户数量的增加,如何设计高效的多用户联合译码方案,优化译码算法以降低计算复杂度,同时提升系统的通信可靠性,是未来研究的重点。
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2025年第51卷第5期
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doi: 10.3969/j.issn.1003-3114.2025.05.020
  • 接收时间:2024-12-09
  • 首发时间:2026-04-17
  • 出版时间:2025-09-18
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  • 收稿日期:2024-12-09
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    1.福州大学 物理与信息工程学院,福建 福州 350116
    2.福州大学 先进制造学院,福建 泉州 362251
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2种不同金属材料的力学参数

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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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