Energy-Efficient Transmission Strategy for UAV-RIS 2.0 Assisted Communications Using Rate Splitting Multiple Access

This study explores the optimization of transmission strategies focusing on energy efficiency within a network comprising ground-based beyond-diagonal reconfigurable intelligent surfaces (BD-RIS), a.k.a RIS 2.0, and multiple unmanned aerial vehicles (UAVs). The motivation behind this work stems from the critical need to enhance energy efficiency in next-generation wireless networks, where the integration of UAVs and RIS technologies presents both opportunities and challenges. Specifically, while UAVs offer flexible deployment and improved coverage, their limited battery life and the complex interference environment in multi-user networks necessitate innovative solutions for sustainable operation. Each UAV is designed to serve its corresponding user group, with each group utilizing unique subcarriers to maintain orthogonality and employing a rate-splitting multiple access (RSMA) strategy within each group. The primary objectives of this work are to optimize: 1) the allocation of BD-RIS elements to groups, 2) the phase rotations of BD-RIS, 3) the common rate allocation in RSMA, 4) UAV trajectories, and 5) the design of precoders. To achieve these objectives, we formulate an optimization problem under the framework of mixed-integer nonlinear programming (MINLP), with a focus on maximizing energy efficiency. Our proposed solution combines generalized Benders decomposition (GBD), a manifold-based algorithm, and successive convex approximation (SCA). GBD decomposes the MINLP into primal and master sub-problems, which are iteratively solved. To efficiently address variable coupling in the primal problem, we adopt a block coordinate descent (BCD) method and employ the Riemannian conjugate gradient (RCG) technique for phase rotation. SCA addresses the remaining challenges in the primal problem, while a two-stage approach simplifies the optimization process. Simulations confirm the significant energy efficiency improvements achieved by the proposed method.

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Publication Details

Journal
IEEE Transactions on Wireless Communications
Published
2025-10-09
DOI
https://doi.org/10.1109/twc.2025.3617169
Primary Topic
UAV Applications and Optimization
Type
article
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article

Energy-Efficient Transmission Strategy for UAV-RIS 2.0 Assisted Communications Using Rate Splitting Multiple Access

Aamer Mohamed Huroon, Yu-Chih Huang, Li‐Chun Wang
IEEE Transactions on Wireless Communications
UAV Applications and Optimization
article

Energy-Efficient Transmission Strategy for UAV-RIS 2.0 Assisted Communications Using Rate Splitting Multiple Access

Aamer Mohamed Huroon, Yu-Chih Huang, Li‐Chun Wang
article en

Abstract

This study explores the optimization of transmission strategies focusing on energy efficiency within a network comprising ground-based beyond-diagonal reconfigurable intelligent surfaces (BD-RIS), a.k.a RIS 2.0, and multiple unmanned aerial vehicles (UAVs). The motivation behind this work stems from the critical need to enhance energy efficiency in next-generation wireless networks, where the integration of UAVs and RIS technologies presents both opportunities and challenges. Specifically, while UAVs offer flexible deployment and improved coverage, their limited battery life and the complex interference environment in multi-user networks necessitate innovative solutions for sustainable operation. Each UAV is designed to serve its corresponding user group, with each group utilizing unique subcarriers to maintain orthogonality and employing a rate-splitting multiple access (RSMA) strategy within each group. The primary objectives of this work are to optimize: 1) the allocation of BD-RIS elements to groups, 2) the phase rotations of BD-RIS, 3) the common rate allocation in RSMA, 4) UAV trajectories, and 5) the design of precoders. To achieve these objectives, we formulate an optimization problem under the framework of mixed-integer nonlinear programming (MINLP), with a focus on maximizing energy efficiency. Our proposed solution combines generalized Benders decomposition (GBD), a manifold-based algorithm, and successive convex approximation (SCA). GBD decomposes the MINLP into primal and master sub-problems, which are iteratively solved. To efficiently address variable coupling in the primal problem, we adopt a block coordinate descent (BCD) method and employ the Riemannian conjugate gradient (RCG) technique for phase rotation. SCA addresses the remaining challenges in the primal problem, while a two-stage approach simplifies the optimization process. Simulations confirm the significant energy efficiency improvements achieved by the proposed method.

IEEE Transactions on Wireless CommunicationsVol. 25
National Yang Ming Chiao Tung University (TW)
Openalex Percentile: Top 62%
UAV Applications and Optimization
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