Joint Computation Offloading and Radio Resource Allocation in MEC-Based Wireless-Powered Backscatter Communication Networks

Abstract

The multi-access edge computing (MEC)-based wireless-powered backscatter communication networks (WP-BackComNets) allow wireless devices (WDs) to offload computation resources to lightweight and widely deployed MEC servers with the assistance of backscatter devices (BDs), which have substantial application prospects for the emerging Internet-of-Things applications. However, the limited battery capacity of WDs is one of the bottlenecks restricting its further development. Reducing the energy consumption and the computation burden of WDs while ensuring the quality-of-service requirements is an urgent issue. To this end, a joint computation offloading and radio resource allocation problem is formulated to minimize the total energy consumption of WDs for an MEC-based WP-BackComNet by jointly optimizing user association, the transmit power and transmission time of WDs, the computational offloading coefficient of each task, and the reflection coefficients of BDs, where the circuit power consumption of BDs, the computational capabilities of WDs, and the task execution delay budgets are considered. To handle this non-convex problem, we propose an efficient algorithm to obtain a suboptimal solution. Simulation results demonstrate that the proposed scheme can effectively decrease the energy consumption compared with the benchmarks.