Joint optimization for STAR-RIS-aided energy-efficient UAV-MEC networks
Author Identifier (ORCID)
Abstract
Unmanned aerial vehicles (UAVs) equipped with multi-access edge computing (MEC) servers have emerged as a promising solution for delivering computation and communication services to intelligent mobile terminals (MTs). The integration of simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) technology further enhances the coverage capabilities of UAVs and introduces greater flexibility into UAV-assisted MEC systems. In this paper, we design a new STAR-RIS-aided energy-efficient UAV-MEC network, where the UAV is equipped with an MEC server and a STAR-RIS, providing the computing services for the tasks form the users and LoS communication services between the BS and users, respectively. Then, we propose a minimal energy consumption problem in the STAR-RIS-aided UAV-MEC network, where the task offloading, the UAV's hovering position, and the STAR-RIS coefficient matrix are jointly optimized. Since the formulated energy minimization problem is non-convex, it is decomposed into two subproblems: a UAV decision subproblem and a STAR-RIS resource allocation subproblem. For the UAV decision subproblem, the offloading ratios and the UAV's hovering position are optimized utilizing the Karush-Kuhn–Tucker (KKT) conditions and the successive convex approximation (SCA), respectively. For the STAR-RIS resource allocation subproblem, the coefficient matrix is optimized via the SCA. Numerical results indicate that the proposed system can significantly reduce energy consumption than the existing benchmarks, i.e., random phase shifts and reflecting-only RIS schemes. Our proposed scheme reduces energy consumption by about 16% and 24% than the random phase shifts and reflecting-only RIS schemes, respectively.
Keywords
multi-access edge computing, resource allocation, simultaneously transmitting and reflecting reconfigurable intelligent surface, task offloading, unmanned aerial vehicle
Document Type
Journal Article
Date of Publication
10-1-2026
Article Number
112655
ISSN
13891286
Volume
289
Publication Title
Computer Networks
Publisher
Elsevier
School
School of Engineering
Funding Information
This work was partly sponsored by Beijing Nova Program (20250484984 ), National Natural Science Foundation of China (62371014 ), and Beijing Natural Science Foundation under Grant (4244065 ).
Copyright
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Recommended Citation
Fang, C., Wang, J., Hu, Z., Xu, H., Zeng, D., Wu, Q., Guo, S., & Ni, W. (2026). Joint optimization for STAR-RIS-aided energy-efficient UAV-MEC networks. Computer Networks, 289, 112655. https://doi.org/10.1016/j.comnet.2026.112655