Performance Analysis of Massive Multi-input and Multi-output with Imperfect Channel State Information

Abstract

The type and state of the fading channel directly affect the performance of massive multi-input and multi-output (MIMO) system. For example, the small and large fading (SSF and LSF) of the channel have a great impact on the sum-rate of the system. However, the channel state information (CSI) is far from perfect, making it difficult to analyze the sum-rate of massive MIMO systems with uniform user distribution. To solve the problem, this paper proposes three scheduling algorithms, namely, semi-orthogonal user scheduling (SUS), random user scheduling (RUS), and distance-dependent user scheduling (DUS). The three algorithms were adopted to schedule different number of users (8, 10 and 12), based on the maximum signalto-noise ratio (SNR) with changing number of base station antennas, number of active users, etc. The zero forcing (ZF) precoding was employed to improve the sum-rate, and the highly scattering Rayleigh fading channel was considered for both SSF and LSF, in the light of user locations. Under imperfect CSI and additional noise, the DUS achieved higher sum-rate than the other algorithms. The research results shed new light on the use of massive MIMO systems for 5G applications with high sum-rate requirements.

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