Energy-Efficient Hybrid Offloading for Backscatter-Assisted Wirelessly Powered MEC with Reconfigurable Intelligent Surfaces

Abstract

We investigate a wireless power transfer (WPT)-based backscatter-mobile edge\ncomputing (MEC) network with a {reconfigurable intelligent surface (RIS)}.In\nthis network, wireless devices (WDs) offload task bits and harvest energy, and\nthey can switch between backscatter communication (BC) and active transmission\n(AT) modes. We exploit the RIS to maximize energy efficiency (EE). To this end,\nwe optimize the time/power allocations, local computing frequencies, execution\ntimes, backscattering coefficients, and RIS phase shifts.} This goal results in\na multi-objective optimization problem (MOOP) with conflicting objectives.\nThus, we simultaneously maximize system throughput and minimize energy\nconsumption via the Tchebycheff method, transforming into two single-objective\noptimization problems (SOOPs). For throughput maximization, we exploit\nalternating optimization (AO) to yield two sub-problems. For the first one, we\nderive closed-form resource allocations. For the second one, we design the RIS\nphase shifts via semi-definite relaxation, a difference of convex functions\nprogramming, majorization minimization techniques, and a penalty function for\nenforcing a rank-one solution. For energy minimization, we derive closed-form\nresource allocations. We demonstrate the gains over several benchmarks. For\ninstance, with a $20$-element RIS, EE can be as high as 3 (Mbits/Joule), a\n150\\% improvement over the no-RIS case (achieving only 2 (Mbits/Joule)).\n