Hybrid Precoding Algorithm for Millimeter-Wave Massive MIMO Systems with Subconnection Structures

Author:

Zhang Xue1,Zhao Feng2ORCID

Affiliation:

1. Key Laboratory of Cognitive Ratio and Information Processing, Guilin University of Electronic Technology, Guilin 541004, China

2. Guangxi Colleges and Universities Key Laboratory of Complex System Optimization and Big Data Processing, Yulin Normal University, Yulin 537000, China

Abstract

In mmWave massive MIMO systems, traditional digital precoding is difficult to be implemented because of the high cost and energy consumption of RF chains. Fortunately, the hybrid precoding which combines digital precoding and analog precoding not only solves this problem successfully, but also improves the performance of the system effectively. However, due to the constant mode constraint introduced by the phase shifter in the analog domain, it is difficult to solve the hybrid precoding directly. There is a solution which divides the total optimization problem into two stages to solve, that is, first fix the digital precoding matrix, solve the analog precoding matrix, and then optimize the digital precoding matrix according to the obtained analog precoding matrix. In this paper, a high energy-efficient hybrid precoding scheme is proposed for the subconnection structure. In the first stage, the optimization problem can be decomposed into a series of subproblems by means of the independent submatrix structure of the analog precoding matrix. When the optimized analog precoding matrix is obtained, the digital precoding matrix can be solved by the minimum mean error (MMSE). Finally, the digital precoding matrix is normalized to satisfy the constraint conditions. The simulation results demonstrate that the performance of the proposed algorithm is close to that of fully digital precoding based on subconnection structure and better than that of the existing algorithms. In addition, this paper presents the simulation analysis of the algorithm performance under imperfect channel state information. Simulation results show that when the estimation accuracy of channel state information is 0.8, the spectral efficiency of the proposed algorithm can already be maintained at a good level.

Funder

Key Science and Technology Project of Guangxi

Publisher

Hindawi Limited

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Information Systems

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