STAR-RIS and UAV Combination for Simultaneous Task Offloading and Communications in MEC Networks

This study investigates a simultaneous tasks of-floading and communications (STOC) strategy in mobile edge computing (MEC) networks, facilitated by the integration of simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) and unmanned aerial vehicles (UAVs). Diverging from conventional MEC approaches, the newly proposed scheme simultaneously accounts for the computational and communicative capacities of MEC networks, rendering it a more pragmatic solution in practice. An optimization problem is devised to maximize the weighted sum of the minimum offloaded task data and communication data, while ensuring the quality of service (QoS) constraints for STOC through joint design of time scheduling, resource allocation, active and passive beamforming, alongside with the UAV trajectory planning. A novel alternating optimization method is proposed to solve this non-convex problem with strong couplings among variables. We provide sufficient numerical results to validate the effectiveness of the proposed STOC scheme.