Simultaneously Transmitting and Reflecting RIS-Aided Mobile Edge Computing: Computation Rate Maximization

TL;DR

This paper explores the use of a novel STAR-RIS technology to enhance multi-user mobile edge computing by optimizing various system parameters, significantly improving computation rates over traditional RIS systems.

Contribution

It introduces a joint optimization framework for STAR-RIS-assisted MEC, including new algorithms for energy splitting and mode switching protocols.

Findings

STAR-RIS significantly outperforms traditional RIS in computation rate.

The proposed algorithms effectively solve non-convex optimization problems.

Simulation results validate the performance gains of STAR-RIS in MEC systems.

Abstract

In this paper, the novel simultaneously transmitting and reflecting (STAR) reconfigurable intelligent surface (RIS), which enables full-space coverage on users located on both sides of the surface, is investigated in the multi-user mobile edge computing (MEC) system. A computation rate maximization problem is formulated via the joint design of the STAR-RIS phase shifts, reflection and transmission amplitude coefficients, the receive beamforming vectors at the access point, and the users' energy partition strategies for local computing and offloading. Two operating protocols of STAR-RIS, namely energy splitting (ES) and mode switching (MS) are studied. Based on DC programming and semidefinite relaxation, an iterative algorithm is proposed for the ES protocol to solve the formulated non-convex problem. Furthermore, the proposed algorithm is extended to solve the non-convex, non-continuous MS problems with binary amplitude coefficients. Simulation results show that the resultant STAR-RIS-aided MEC system significantly improves the computation rate compared to the baseline scheme with conventional reflect-only/transmit-only RIS.