Massive MIMO-OFDM Receiver Design Based on Hidden Cluster Hypothesis and Dirichlet Process
CUI Jian-hua1, YUAN Zheng-dao2,3, WANG Zhong-yong3, LU Xin-hua3, XUE Qi3
1. School of Physics and Electronic Information, Luoyang Normal University, Luoyang, Henan 471934, China;
2. Postdoctoral Workstation, Henan TV & Radio University, Zhengzhou, Henan, 450001;
3. School of Information Engineering, Zhengzhou University, Zhengzhou, Henan 450001, China
Abstract:The paper discusses the spatial correlation of channels in massive MIMO-OFDM system,and proposes a hidden clustering hypothesis to simulations different propagation environments with probability parameters.Then,the Dirichlet process (DP) in machine learning is introduced into sparse Bayesian learning (SBL) model and a DP-SBL structure is established.Consequently,the hidden clustering features of massive MIMO system are explored simultaneously in the process of channel estimation.Furthermore,the DP-SBL structure is applied to massive MIMO-OFDM systems,and a receiver algorithm based on hidden clustering and Dirichlet process is deduced by using message passing algorithm on factor graphs.Finally,we compare the proposed algorithm with the existing algorithms.Simulation results show that the proposed algorithm can exploit and utilize the spatial resources of massive MIMO-OFDM system.It can achieve remarkable performance gain with low computation complexity and strong robustness.
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