宽带大规模MIMO-OFDM的联合差分信道估计方案  

Sparse Channel Estimation Scheme Based on Joint Difference for Broadband Massive MIMO OFDM

作　　者：黄灿 李素月[1] HUANG Can;LI Su-yue(School of Electronic Information Engineering, Taiyuan University of Science and Technology,Taiyuan 030024,China)

机构地区：[1]太原科技大学电子信息工程学院,太原030024

出　　处：《太原科技大学学报》2018年第6期411-417,共7页Journal of Taiyuan University of Science and Technology

基　　金：国家自然科学青年基金(61501315);山西省高等学校科技创新项目(2015169);校博士启动金(20142005)

摘　　要：鉴于大规模多输入多输出正交频分复用(Massive MIMO OFDM)下行链路无线通信系统,提出一种基于空时共同稀疏性的信道估计重构算法。所提算法在子空间追踪(SP)算法的基础上,利用信道的时间相关性和多天线的共同稀疏性,同时考虑联合差分和结构稀疏进一步降低导频开销并提升估计性能。提出的联合差分结构化子空间追踪(Joint Differential Structured SP,JDSSP)算法特点如下:第一,算法在每一次迭代过程中同时对多个向量进行更新,对稀疏性进行结构化增强,提升算法的重构性能。第二,算法在进行重构过程中,并不是只处理当前时刻接收到的导频信号,而是联合前一帧的导频信号进行差分,进一步增强稀疏性,进而提升算法重构的精度。仿真结果表明,所提算法在降低导频开销的同时能够取得较好的参数估计性能。In order to solve the problem of massive MIMO OFDM downlink mobile communication system,a new channel estimation algorithm based on space-time common sparsity is proposed.The proposed SP-based algorithm will further reduce the pilot overhead and improve performance,utilizing space-time common sparsity while considering joint difference and structured sparse.The proposed Joint Differential Structured Subspace Pursuit algorithm(JDSSP)characteristics are as follows:First,in every iteration process of the algorithm,multiple vectors are simultaneously updated,sparse structure is enhanced,performance of reconstruction is improved.Secondly,the pilot signal received now makes joint difference with the previous pilot signal in the process of reconstruction,instead of current single process of the pilot.The simulation results show that the proposed algorithm can achieve better performance in reducing the pilot overhead.

关 键 词：大规模MIMO 正交频分复用 压缩感知 联合差分 稀疏信道估计 

分 类 号：TN914[电子电信—通信与信息系统]