A channel estimation algorithm for large-scale MIMO system using block sparsity adaptive matching pursuit

作     者：Chen, Liyan 

作者机构：Anyang Presch Educ Coll Dept Presch Educ Anyang 456150 Henan Peoples R China 

出 版 物：《INTERNATIONAL JOURNAL OF AUTONOMOUS AND ADAPTIVE COMMUNICATIONS SYSTEMS》 (国际自主性与自适应通信系统杂志)

年 卷 期：2021年第14卷第1-2期

页      面：132-150页

核心收录：

学科分类：0810[工学-信息与通信工程] 0808[工学-电气工程] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：channel estimation algorithm multiple input multiple output (MIMO) system adaptive beamforming BSAMP block sparsity adaptive matching pursuit energy dispersion sparse matrix 

摘      要：A new adaptive channel estimation algorithm for large-scale multiple input multiple output (MIMO) systems is proposed by combining the block sparsity adaptive matching pursuit (BSAMP) technique with adaptive beamforming. Firstly, the structure model based on continuous constant is optimised randomly, and it is used alternately with the basic denoising optimisation scheme to find the sparse characteristic channel. Then the sparse matrix is optimised based on adaptive beamforming to enhance the channel sparsity. Furthermore, based on BSAMP technology, using the joint sparsity of large-scale MIMO system subchannels, we set threshold and find the maximum backward difference position to select the atoms of the support set quickly and preliminarily. At the same time, the energy dispersion caused by the non-orthogonality of the observation matrix is considered to improve the estimation performance of the algorithm. Finally, the atoms are filtered by regularisation to improve the stability of the algorithm. Simulation results show that the algorithm can recover large-scale MIMO channel information with unknown sparsity quickly and accurately, and the average running time is only 0.12 s.