Compressed Sensing Based Channel Estimation for Movable Antenna Communications

TL;DR

This paper introduces a compressed sensing-based method for efficient channel estimation in movable antenna systems, enabling accurate channel response reconstruction with reduced pilot overhead and computational complexity.

Contribution

A novel successive transmitter-receiver compressed sensing (STRCS) method that exploits multi-path component representation for improved channel estimation in movable antenna communications.

Findings

Outperforms benchmark schemes in pilot overhead reduction.

Achieves higher channel reconstruction accuracy.

Demonstrates effectiveness through simulation results.

Abstract

In this letter, we study the channel estimation for wireless communications with movable antenna (MA), which requires to reconstruct the channel response at any location in a given region where the transmitter/receiver is located based on the channel measurements taken at finite locations therein, so as to find the MA's location for optimizing the communication performance. To reduce the pilot overhead and computational complexity for channel estimation, we propose a new successive transmitter-receiver compressed sensing (STRCS) method by exploiting the efficient representation of the channel responses in the given transmitter/receiver region (field) in terms of multi-path components. Specifically, the field-response information (FRI) in the angular domain, including the angles of departure (AoDs)/angles of arrival (AoAs) and complex coefficients of all significant multi-path components are sequentially estimated based on a finite number of channel measurements taken at random/selected locations by the MA at the transmitter and/or receiver. Simulation results demonstrate that the proposed channel reconstruction method outperforms the benchmark schemes in terms of both pilot overhead and channel reconstruction accuracy.