Broadband Channel Estimation for Movable Antenna Systems via Compressive Sensing

This paper proposes a novel channel estimation method for multicarrier movable antenna (MA) systems based on the OMP algorithm. The channel model of the MA communication system can be described using delay, angle of arrival (AoA), and angle of departure (AoD). Thus, the paper employs compressive sensing (CS) to jointly estimate sparse angles and delays, addressing the channel estimation challenges in multicarrier MA communication systems. Due to delay estimation being taken into consideration, the channel estimation performance improves compared to using only angle estimation. Joint estimation ensures that the estimated angles and delays correspond to each other. The simulation results show that channel estimation performance in the 2D AoAs/AoDs-delay domain significantly outperforms that in the 1D AoAs/AoDs domain. Furthermore, simulations show that the channel estimation gain approaches its upper limit as the number of MA positions increases.

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Publication Details

Published
2025-08-10
DOI
https://doi.org/10.1109/iccc65529.2025.11149143
Primary Topic
Advanced MIMO Systems Optimization
Type
article
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article

Broadband Channel Estimation for Movable Antenna Systems via Compressive Sensing

Chao Sun, Ziwei Wan, Zhen Gao, Yining Li
Advanced MIMO Systems Optimization
article

Broadband Channel Estimation for Movable Antenna Systems via Compressive Sensing

Chao Sun, Ziwei Wan, Zhen Gao, Yining Li
article en

Abstract

This paper proposes a novel channel estimation method for multicarrier movable antenna (MA) systems based on the OMP algorithm. The channel model of the MA communication system can be described using delay, angle of arrival (AoA), and angle of departure (AoD). Thus, the paper employs compressive sensing (CS) to jointly estimate sparse angles and delays, addressing the channel estimation challenges in multicarrier MA communication systems. Due to delay estimation being taken into consideration, the channel estimation performance improves compared to using only angle estimation. Joint estimation ensures that the estimated angles and delays correspond to each other. The simulation results show that channel estimation performance in the 2D AoAs/AoDs-delay domain significantly outperforms that in the 1D AoAs/AoDs domain. Furthermore, simulations show that the channel estimation gain approaches its upper limit as the number of MA positions increases.

Beijing Institute of Technology (CN)
Openalex Percentile: Top 77%
Advanced MIMO Systems Optimization
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