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Computing Capability Optimization for STAR-RIS-Assisted WP-NOMA-MEC Systems
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DOI：10.1109/LCOMM.2025.3639678.png)
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Abstract
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In this letter, we investigate a wireless-powered mobile edge computing (WP-MEC) system, and propose a simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS)-assisted non-orthogonal multiple access (NOMA) scheme, referred to as SRIS-NOMA. In the proposed SRIS-NOMA scheme, with the assistance of the STAR-RIS, multiple passive users first harvest energy from a power station (PS) and then leverage the harvested energy for local computation and task offloading to the base station (BS). To maximize total computation bits (TCB) of the SRIS-NOMA scheme, we jointly design the time allocation, local computing frequency (LCF), users’ transmit power, BS’s receive beamforming (BRB), and the STAR-RIS coefficients. Specifically, the optimal time allocation solution is determined by one-dimensional search, while closed-form solutions for LCF, users’ transmit power, and the BRB vector are derived, and efficient solutions for the STAR-RIS coefficients are obtained using the successive convex approximation (SCA) method. Simulation results demonstrate that the proposed SRIS-NOMA scheme surpasses the benchmarks in terms of TCB performance.
Keywords:
Wireless power transfer
mobile edge computing
simultaneously transmitting and reflecting reconfigurable intelligent surface
successive convex approximation
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