Robust Precoding for FDD MISO Systems via Minorization Maximization

TL;DR

This paper introduces a robust precoding method for FDD MISO systems that optimizes spectral efficiency while accounting for channel estimation errors, improving computational speed and performance under imperfect CSI.

Contribution

It presents a novel minorization maximization-based approach for robust precoder design that eliminates the need for line search, enhancing efficiency and robustness against CSI errors.

Findings

Competitive with WMMSE precoding under imperfect CSI

Eliminates line search for power constraint satisfaction

Accelerates precoder computation

Abstract

In this work, we propose an approach to robust precoder design based on a minorization maximization technique that optimizes a surrogate function of the achievable spectral efficiency. The presented method accounts for channel estimation errors during the optimization process and is, hence, robust in the case of imperfect channel state information (CSI). Additionally, the design method is adapted such that the need for a line search to satisfy the power constraint is eliminated, that significantly accelerates the precoder computation. Simulation results demonstrate that the proposed robust precoding method is competitive with weighted minimum mean square error (WMMSE) precoding, in particular, under imperfect CSI scenarios.