MIMO Transmission Under Discrete Input Signal Constraints

TL;DR

This paper introduces a joint optimization framework for MIMO transmission that improves mutual information and approaches the Shannon limit by optimizing precoders and input distributions under discrete signal constraints.

Contribution

It presents a unified approach to jointly optimize MIMO precoders and discrete input distributions, advancing beyond existing strategies that assume uniform inputs.

Findings

Achieves higher mutual information closer to Shannon limit

Reduces frame error rate in simulations

Outperforms existing MIMO strategies in numerical tests

Abstract

In this paper, we propose a multiple-input multipleoutput (MIMO) transmission strategy that is closer to the Shannon limit than the existing strategies. Different from most existing strategies which only consider uniformly distributed discrete input signals, we present a unified framework to optimize the MIMO precoder and the discrete input signal distribution jointly. First, a general model of MIMO transmission under discrete input signals and its equivalent formulation are established. Next, in order to maximize the mutual information between the input and output signals, we provide an algorithm that jointly optimizes the precoder and the input distribution. Finally, we compare our strategy with other existing strategies in the simulation. Numerical results indicate that our strategy narrows the gap between the mutual information and Shannon limit, and shows a lower frame error rate in simulation.