通信学报2017，Vol.38Issue(12)：57-62,6.DOI:10.11959/j.issn.1000-436x.2017291
大规模MIMO系统稀疏度自适应信道估计算法
Sparsity adaptive channel estimation algorithm based on compressive sensing for massive MIMO systems
摘要
Abstract
A sparsity-adaptive channel estimation algorithm based on compressive sensing was proposed for massive MIMO systems when the number of channel multi-paths was unknown.By exploiting the joint sparsity characteristics of the sub-channels,the proposed block sparsity adaptive matching pursuit(BSAMP)algorithm first selected atoms by set-ting a threshold and finding the position of the maximum backward difference,which reduces the energy dispersion caused by the non-orthogonality of the observation matrix and improves the performance of the algorithm.Then a regula-rization method was utilized to improve the stability of the algorithm.Simulation results demonstrate that the proposed algorithm recovers the channel state information accurately and shows a high computational efficiency.关键词
大规模MIMO/压缩感知/信道估计/稀疏度自适应Key words
massive MIMO/compressive sensing/channel estimation/sparsity adaptive分类
信息技术与安全科学引用本文复制引用
戈立军,郭徽,李月,赵澜..大规模MIMO系统稀疏度自适应信道估计算法[J].通信学报,2017,38(12):57-62,6.基金项目
国家自然科学基金资助项目(No.61302062) （No.61302062）
天津市应用基础及前沿技术研究计划青年基金资助项目(No.13JCQNJC00900)The National Natural Science Foundation of China (No.61302062),The Research Program of Application Foundation and Advanced Technology of Tianjin for Young Scientist (No.13JCQNJC00900) （No.13JCQNJC00900）
