MIMO Capacity Characterization for Movable Antenna Systems

TL;DR

This paper introduces a movable antenna MIMO system that optimizes antenna positions to significantly enhance channel capacity, offering a flexible alternative to fixed antennas and demonstrating substantial performance improvements.

Contribution

It develops an optimization framework for antenna position and signal covariance to maximize capacity, including efficient algorithms and insights into capacity gains over fixed systems.

Findings

Movable antennas significantly improve MIMO capacity.

Proposed algorithms effectively optimize antenna positions.

Numerical results confirm capacity gains over traditional fixed systems.

Abstract

In this paper, we propose a new multiple-input multiple-output (MIMO) communication system with movable antennas (MAs) to exploit the antenna position optimization for enhancing the capacity. Different from conventional MIMO systems with fixed-position antennas (FPAs), the proposed system can flexibly change the positions of transmit/receive MAs, such that the MIMO channel between them is reconfigured to achieve higher capacity. We aim to characterize the capacity of MA-enabled point-to-point MIMO communication systems, by jointly optimizing the positions of transmit and receive MAs as well as the covariance of transmit signals. First, we develop an efficient alternating optimization algorithm to find a locally optimal solution by iteratively optimizing the transmit covariance matrix and the position of each transmit/receive MA with the other variables being fixed. Next, we propose alternative algorithms of lower complexity for capacity maximization in the low-SNR regime and for the multiple-input single-output (MISO) and single-input multiple-output (SIMO) cases. Numerical results show that our proposed MA systems significantly improve the MIMO channel capacity compared to traditional FPA systems as well as various benchmark schemes, and useful insights are drawn into the capacity gains of MA systems.