首页|压缩感知辅助的低复杂度SCMA系统优化设计

压缩感知辅助的低复杂度SCMA系统优化设计

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稀疏码多址接入(SCMA)技术是一项备受重视的基于码域的非正交多址接入(NOMA)技术.针对现有SCMA码本设计中未能结合数据和解码器性质以及MPA复杂度较高的问题,该文提出一种压缩感知辅助的低复杂度 SCMA系统优化设计方案.首先以系统误码率为优化目标,设计一种码本自更新方法用于实现低复杂度检测器,该方法在稀疏向量重构训练过程中使用梯度下降法实现码本的自更新.其次,设计一种压缩感知辅助的多用户检测算法:符号判决正交匹配追踪(SD-OMP)算法.通过在发射端对发射信号进行稀疏化处理,在接收端利用压缩感知技术对多用户的稀疏信号进行高效的检测和重构,达到减少用户间的冲突和降低系统复杂度的目的.仿真结果表明,在高斯信道条件下,压缩感知辅助的低复杂度SCMA系统优化设计方案能够有效降低多用户检测的复杂度,且在系统用户部分活跃时能够表现出较好的误码率性能.
Optimized Design of Low Complexity SCMA System Assisted by Compressed Sensing
Sparse Code Multiple Access(SCMA)technology is a highly valued code domain-based Non-Orthogonal Multiple Access(NOMA)technology.In order to solve the problem that the existing SCMA codebook design fails to combine the properties of data and decoder and the high complexity of MPA,a compressed sensing-assisted low-complexity SCMA system optimization design scheme is proposed.First,a codebook self-updating method is designed based on the system bit error rate optimization goal,which uses the gradient descent method to achieve self-updating of the codebook during the sparse vector reconstruction training process.Second,a compressed sensing-assisted multi-user detection algorithm is designed:Sign Decision Orthogonal Matching Pursuit(SD-OMP)algorithm.By sparse processing of the transmitted signal at the transmitting end,the compressed sensing technology is used at the receiving end to efficiently detect and reconstruct multi-user sparse signals,this results in a reduction of conflicts between users and a reduction in system complexity.The simulation results show that under Gaussian channel conditions,the compressed sensing-assisted low-complexity SCMA system optimization and design scheme can effectively reduce the complexity of multi-user detection,and can show better bit error rate performance when the system user part is active.

Sparse Code Multiple Access(SCMA)Compressed sensingCodebook designMulti-user detectionLow complexity

余礼苏、钟润、吕欣欣、王玉皞、王正海

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南昌大学信息工程学院 南昌 330031

稀疏码多址接入 压缩感知 码本设计 多用户检测 低复杂度

国家自然科学基金国家自然科学基金国家自然科学基金江西省主要学科学术和技术带头人省级人才项目江西省自然科学基金中国博士后科学基金中国博士后科学基金计算机体系结构国家重点实验室开放基金

62161024620610306216102320232BCJ2308520224BAB2120022021TQ01362022M711463CARCHB202019

2024

10.11999/JEIT231226

电子与信息学报
中国科学院电子学研究所 国家自然科学基金委员会信息科学部

电子与信息学报

CSTPCD北大核心
影响因子：1.302
ISSN：1009-5896
年,卷(期)：2024.46(5)