Energy-Efficient Transmission Strategy for UAV-RIS 2.0 Assisted Communications Using Rate Splitting Multiple Access
Author(s) -
Aamer Mohamed Huroon,
Yu-Chih Huang,
Li-Chun Wang
Publication year - 2025
Publication title -
ieee transactions on wireless communications
Language(s) - English
Resource type - Magazines
SCImago Journal Rank - 2.01
H-Index - 223
eISSN - 1558-2248
pISSN - 1536-1276
DOI - 10.1109/twc.2025.3617169
Subject(s) - communication, networking and broadcast technologies , computing and processing , signal processing and analysis
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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