Movable Antenna-Enabled Full-Duplex Multiuser Communications

Movable antenna (MA) has emerged as a promising technology to enhance the performance of wireless communication systems by enabling flexible antenna movement. In this paper, we investigate a novel full-duplex system enabled by movable antennas (MAs), where a full-duplex base station (BS) is equipped with transmit and receive MA arrays to serve multiple downlink and uplink users. We aim to maximize the sum of achievable rates by jointly optimizing the MA positions, receive combining vectors, transmit beamformers, and uplink transmit power. To tackle this non-convex optimization problem, we propose an efficient algorithm based on particle swarm optimization (PSO) and successive convex approximation (SCA). Simulation results validate the effectiveness of the proposed scheme and provide valuable insights for practical applications.

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Publication Details

Published
2025-05-23
DOI
https://doi.org/10.1109/iwrfat65352.2025.11102911
Citations
1
Primary Topic
Full-Duplex Wireless Communications
Type
article
Field-Weighted Citation Impact
0.73
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article

Movable Antenna-Enabled Full-Duplex Multiuser Communications

Jingze Ding, Bingli Jiao, Xiaohui Jia, Zijian Zhou et al.
1 citations
Full-Duplex Wireless Communications
0.73
article

Movable Antenna-Enabled Full-Duplex Multiuser Communications

Jingze Ding, Bingli Jiao, Xiaohui Jia, Zijian Zhou, Lifeng Lin
article en
1 citations

Abstract

Movable antenna (MA) has emerged as a promising technology to enhance the performance of wireless communication systems by enabling flexible antenna movement. In this paper, we investigate a novel full-duplex system enabled by movable antennas (MAs), where a full-duplex base station (BS) is equipped with transmit and receive MA arrays to serve multiple downlink and uplink users. We aim to maximize the sum of achievable rates by jointly optimizing the MA positions, receive combining vectors, transmit beamformers, and uplink transmit power. To tackle this non-convex optimization problem, we propose an efficient algorithm based on particle swarm optimization (PSO) and successive convex approximation (SCA). Simulation results validate the effectiveness of the proposed scheme and provide valuable insights for practical applications.

Fujian Normal University (CN), Peking University (CN), Chinese University of Hong Kong, Shenzhen (CN), Fujian University of Technology (CN)
Affordable and clean energy
Openalex Percentile: Top 25%
Full-Duplex Wireless Communications
0.73
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