Energy-Efficient Beamforming for Massive MIMO with Inter-Cell Interference and Inaccurate CSI

Abstract

Massive MIMO is one of the important technologies for the 5G cellular communications. It boasts to greatly increase the spectrum efficiency through aggressive spatial multiplexing, consuming a much lower antenna power. However, fully exploiting the capability of Massive MIMO requires accurate channel state information (CSI) at base stations (BSs). Obtaining accurate CSI is quite challenging in a heterogeneous networking context or a fast-changing urban environment; the limited supply of pilot signal versus increased number of users also contributes to the errors in channel state estimation. Another challenge in massive MIMO is that most of the existing precoding algorithms for interference mitigation consider only intra-cell interference, but overlook the impact of inter-cell interference. In this paper we propose a beamforming scheme accounting for both issues — CSI error and inter-cell interference, with the objective of maximizing system energy efficiency. This problem has many coupling non-convex constraints and is intractable to solve directly. We investigate the use of a sequential convex approximation (SCA) algorithm. It solves a series of approximated convex subproblems, and provably arrives at a stationary solution to the original problem. Compared with the commonly used but oversimplified semidefinite relaxation, numerical results demonstrate that SCA algorithm can guarantee solution feasibility with robust performance, at the cost of moderately increased computation complexity.