Movable Antenna Array for Improving AAV Relaying Networks

Recently, movable antenna (MA) has become a prominent research topic in wireless communications due to the flexible mechanical movement. In this letter, a MA-assisted unmanned aerial vehicle (UAV) relaying framework is proposed, where the UAV relay delivers the information from a source node (SN) to multiple destination nodes (DNs). The goal is to maximize the total throughput of DNs, by jointly optimizing beamforming, time slot allocation, antenna position, and UAV trajectory. To solve the highly complex non-convex problem, we propose an efficient penalty-based alternating optimization algorithm. Specifically, the successive convex approximation technique is adopted to deal with the non-convex constraints, and the penalized method is exploited to handle the rank-one constraints. Numerical results demonstrate that the MA outperforms the conventional fixed-position antenna (FPA), and the proposed algorithm significantly enhances network throughput compared to other benchmark schemes.

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Publication Details

Journal
IEEE Wireless Communications Letters
Published
2025-09-24
DOI
https://doi.org/10.1109/lwc.2025.3614489
Citations
2
Primary Topic
Antenna Design and Analysis
Type
article
Field-Weighted Citation Impact
9.99
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article

Movable Antenna Array for Improving AAV Relaying Networks

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2 citations
IEEE Wireless Communications Letters
Antenna Design and Analysis
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article

Movable Antenna Array for Improving AAV Relaying Networks

Dingcheng Yang, Yu Xu, Wenqiang Zhou, Fahui Wu, Lin Xiao, Tiankui Zhang
article en
2 citations

Abstract

Recently, movable antenna (MA) has become a prominent research topic in wireless communications due to the flexible mechanical movement. In this letter, a MA-assisted unmanned aerial vehicle (UAV) relaying framework is proposed, where the UAV relay delivers the information from a source node (SN) to multiple destination nodes (DNs). The goal is to maximize the total throughput of DNs, by jointly optimizing beamforming, time slot allocation, antenna position, and UAV trajectory. To solve the highly complex non-convex problem, we propose an efficient penalty-based alternating optimization algorithm. Specifically, the successive convex approximation technique is adopted to deal with the non-convex constraints, and the penalized method is exploited to handle the rank-one constraints. Numerical results demonstrate that the MA outperforms the conventional fixed-position antenna (FPA), and the proposed algorithm significantly enhances network throughput compared to other benchmark schemes.

IEEE Wireless Communications LettersVol. 14(12)
Beijing University of Posts and Telecommunications (CN), Nanchang University (CN)
Openalex Percentile: Top 2%
Antenna Design and Analysis
9.99
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