Optimization algorithm for joint sparse hybrid precoding in millimeter wave massive MIMO systems
(1. School of Internet of Things Engineering, Jiangnan University, Wuxi, Jiangsu 214122, China; 2. Jiangsu Future Networks Innovation Institute, Nanjing, Jiangsu 211111, China)
Abstract：To improve the spectral efficiency and bit error ratio performance in the millimeter wave massive multiple input multiple output (MIMO) systems, a hybrid precoding optimization algorithm was proposed based on joint sparsity. According to the sparseness property of the millimeter wave channel in the angular domain, the lobe channel was reconstructed, and the hybrid precoding design was divided into multiple sub-problems for each lobe subchannel. To solve the sparse reconstruction problem with nonconvex constraints, the implicit sparse structure of digital precoding matrix was used to design the self-support set and common support set of analog precoding matrix for each data stream. Based on the correlation between analog precoding matrix and digital precoding matrix, the analog precoder and the digital precoder were jointly optimized. The computation complexity analysis and simulation analysis were completed. The results show that compared with the OMP algorithm, the proposed algorithm exhibits remarkable 91% or 93% reduction in computational complexity with enhancing spectral efficiency and bit error ratio performance when compared to the SLD algorithm.
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