A Unified Linear MSE Minimization MIMO Beamforming Design Based on Quadratic Matrix Programming

TL;DR

This paper presents a unified approach to MIMO beamforming design that minimizes mean-square-error across various wireless systems using quadratic matrix programming, simplifying the optimization process.

Contribution

It introduces a comprehensive framework leveraging quadratic matrix programming for unified MIMO beamforming design across multiple wireless system types.

Findings

MSE minimization problems can be solved via QMP in diverse wireless systems.

A unified framework simplifies the design process for MIMO beamforming.

The approach is applicable to multi-cell, multi-user, cognitive radio, and relaying systems.

Abstract

In this paper, we investigate a unified linear transceiver design with mean-square-error (MSE) as the objective function for a wide range of wireless systems. The unified design is based on an elegant mathematical programming technology namely quadratic matrix programming (QMP). It is revealed that for different wireless systems such as multi-cell coordination systems, multi-user MIMO systems, MIMO cognitive radio systems, amplify-and-forward MIMO relaying systems, the MSE minimization beamforming design problems can always be solved by solving a number of QMP problems. A comprehensive framework on how to solve QMP problems is also given.