The Capacity of the Amplitude-Constrained Vector Gaussian Channel

TL;DR

This paper investigates the capacity limits of vector Gaussian channels with amplitude constraints, providing new insights into optimal input distributions and an iterative method for capacity evaluation.

Contribution

It introduces novel insights into capacity-achieving inputs and an iterative algorithm for capacity and distribution computation under amplitude constraints.

Findings

Characterization of capacity-achieving input distributions

Development of an iterative algorithm for capacity evaluation

Enhanced understanding of amplitude-constrained MIMO channels

Abstract

The capacity of multiple-input multiple-output additive white Gaussian noise channels is investigated under peak amplitude constraints on the norm of the input vector. New insights on the capacity-achieving input distribution are presented. Furthermore, it is provided an iterative algorithm to numerically evaluate both the information capacity and the optimal input distribution of such channel.