Robust Joint Precoder and Equalizer Design in MIMO Communication Systems

TL;DR

This paper proposes a robust joint precoder and equalizer design for MIMO systems that accounts for uncertainties in channel and interference knowledge, transforming the problem into a convex optimization with a closed-form solution.

Contribution

It introduces a worst-case robust optimization framework for joint precoder and equalizer design in MIMO systems with imperfect information, providing a closed-form solution approach.

Findings

Derivation of worst-case matrices for uncertainties.

Transformation of the problem into a convex scalar optimization.

Development of an iterative algorithm for robust transceiver design.

Abstract

We address joint design of robust precoder and equalizer in a MIMO communication system using the minimization of weighted sum of mean square errors. In addition to imperfect knowledge of channel state information, we also account for inaccurate awareness of interference plus noise covariance matrix and power shaping matrix. We follow the worst-case model for imperfect knowledge of these matrices. First, we derive the worst-case values of these matrices. Then, we transform the joint precoder and equalizer optimization problem into a convex scalar optimization problem. Further, the solution to this problem will be simplified to a depressed quartic equation, the closed-form expressions for roots of which are known. Finally, we propose an iterative algorithm to obtain the worst-case robust transceivers.