Energy Efficiency Maximization for RIS-UAVs Aided Communication Networks: A Joint Optimization Framework

Authors: Guo, X., Zhao, P., Zhang, J., Song, Y., Chen, S.

Journal: IEEE Wireless Communications Letters

Publication Date: 01/01/2026

Volume: 15

Pages: 4440-4444

eISSN: 2162-2345

ISSN: 2162-2337

DOI: 10.1109/LWC.2026.3717056

Abstract:

In this letter, we propose an efficient resource allocation algorithm for communication systems assisted by multiple uncrewed aerial vehicles borne reconfigurable intelligent surfaces (RISs). The algorithm jointly optimizes the base station (BS) power allocation, active beamforming and RIS phase shifts to maximize the system energy efficiency (EE). As the EE maximization problem is a multi-variable coupling problem with non-convexity, we adopt a Dinkelbach-based block coordinate descent framework to decouple it into three subproblems. The BS power allocation and active beamforming subproblems are solved using fractional programming and Riemannian conjugate gradient algorithm, respectively. For the RIS phase shifts optimization, we propose a low-complexity momentum-accelerated coordinate descent algorithm. Numerical results validate the effectiveness of our joint optimization framework.

https://eprints.bournemouth.ac.uk/42249/

Source: Scopus