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A simultaneously transmitting and reflecting reconfigurable intelligentsurface (STAR-RIS) enhanced unnamed aerial vehicle (UAV)-enabled multi-usermobile edge computing (MEC) scheme is proposed in this paper. Different fromthe existing MEC works, the proposed scheme allows bi-directional offloadingwhere users can simultaneously offload their computing tasks to the MEC serverssituated at the ground base station (BS) and aerial UAV with the assistance ofthe STARRIS. Specifically, we formulate an optimization problem aiming atmaximizing the energy efficiency of the system while ensuring the quality ofservice (QoS) constraint by jointly optimizing the resource allocation, userscheduling, passive beamforming of the STAR-RIS, and the UAV trajectory. Aniterative algorithm designed with the Dinkelbach's algorithm and the successiveconvex approximation (SCA) is proposed to effectively handle the formulatednon-convex optimization problem. Simulation results indicate that the proposedSTAR-RIS enhanced UAV-enabled MEC scheme possesses significant advantages inenhancing the system energy efficiency over other baseline schemes includingthe conventional RIS-aided scheme.

STAR-RIS Enhanced UAV-Enabled MEC Networks with Bi-Directional Task Offloading