Robust Transmission for Massive MIMO Downlink with Imperfect CSI

TL;DR

This paper develops robust linear precoders for massive MIMO downlink systems with imperfect CSI, optimizing spectral efficiency under realistic channel models and errors.

Contribution

It introduces a novel robust precoder design combining MM algorithm and deterministic equivalents, including low-complexity algorithms for practical implementation.

Findings

Achieves high spectral efficiency in various mobile scenarios.

Proves beam domain transmission is optimal when channel means are zero.

Provides algorithms with reduced computational complexity.

Abstract

In this paper, the design of robust linear precoders for the massive multi-input multi-output (MIMO) downlink with imperfect channel state information (CSI) is investigated. The imperfect CSI for each UE obtained at the BS is modeled as statistical CSI under a jointly correlated channel model with both channel mean and channel variance information, which includes the effects of channel estimation error, channel aging and spatial correlation. The design objective is to maximize the expected weighted sum-rate. By combining the minorize-maximize (MM) algorithm with the deterministic equivalent method, an algorithm for robust linear precoder design is derived. The proposed algorithm achieves a stationary point of the expected weighted sum-rate maximization problem. To reduce the computational complexity, two low-complexity algorithms are then derived. One for the general case, and the other for the case when all the channel means are zeros. For the later case, it is proved that the beam domain transmission is optimal, and thus the precoder design reduces to the power allocation optimization in the beam domain. Simulation results show that the proposed robust linear precoder designs apply to various mobile scenarios and achieve high spectral efficiency.