STAR-RIS-assisted UAV-enabled MEC network: Minimizing long-term latency and system stability optimization

Abstract

Unmanned aerial vehicle (UAV)-assisted wireless power transfer (WPT) is a promising technology for delivering sustainable energy to energy-constrained ground users (GUs) in mobile edge computing (MEC) networks. Nevertheless, the network performance is severely limited by channel fading. Compared with the conventional reconfigurable intelligent surface (RIS) limited to half-space coverage, the simultaneously transmitting and reflecting (STAR)-RIS achieves full-space coverage, thereby enhancing both WPT efficiency and computational task offloading performance. To fully investigate the potential of STAR-RIS, this paper proposes a STAR-RIS-assisted UAV-enabled MEC system aiming to minimize long-term latency while ensuring system stability by jointly optimizing time slot allocation, STAR-RIS coefficient matrices, and UAV trajectory. By leveraging the Lyapunov optimization method, the original long-term stochastic optimization problem is transformed into tractable deterministic sub-problems, which are then solved by using successive convex approximation, penalty functions, and convex optimization techniques. Simulation results demonstrate that the proposed scheme effectively balances long-term latency reduction and system stability, achieving significant performance gains compared with baseline schemes.