TY  - INPR
Y1  - 2025/01/23/
AV  - public
TI  - Energy-Efficient STAR-RIS Enhanced UAV-Enabled MEC Networks with Bi-Directional Task Offloading
N1  - This version is the author accepted manuscript. For information on re-use, please refer to the publisher?s terms and conditions.
UR  - https://doi.org/10.1109/twc.2025.3529252
PB  - Institute of Electrical and Electronics Engineers (IEEE)
SN  - 1536-1276
N2  - This paper introduces a novel multi-user mobile edge computing (MEC) scheme facilitated by a simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) and a unmanned aerial vehicle (UAV). Unlike existing MEC approaches, the proposed scheme enables bi-directional offloading, allowing users to concurrently offload tasks to the MEC servers located at ground base station (BS) and UAV with the support of the STAR-RIS. To evaluate the effectiveness of the proposed MEC scheme, we first formulate an optimization problem aiming at maximizing the energy efficiency of the system while ensuring the quality of service (QoS) constraints by jointly optimizing the resource allocation, user scheduling, passive beamforming of the STAR-RIS, and the UAV trajectory. A block coordinate descent (BCD) iterative algorithm designed with the Dinkelbach?s algorithm and the successive convex approximation (SCA) technique is proposed to effectively handle the formulated non-convex optimization problem characterized by significant coupling among variables. Simulation results indicate that the proposed STAR-RIS enhanced UAV-enabled MEC scheme possesses significant advantages in enhancing the system energy efficiency over other baseline schemes including the conventional RIS-aided scheme.
ID  - discovery10204328
A1  - Xiao, Han
A1  - Hu, Xiaoyan
A1  - Zhang, Weile
A1  - Wang, Wenjie
A1  - Wong, Kai-Kit
A1  - Yang, Kun
KW  - STAR-RIS; unmanned aerial vehicle (UAV);
mobile edge computing (MEC); energy efficiency
JF  - IEEE Transactions on Wireless Communications
ER  -