Quantum Optimization for Bidirectional Telecom Energy Exchange and Vehicular Edge Computing in Green 6G Networks
Ferheen Ayaz, Maziar Nekovee · 2024
The latest 6G innovations envision various global benefits beyond connectivity. One of the pressing issues which can be potentially addressed by 6G is environment sustainability and reaching net-zero. Recent research proposes 6G-enabled communications for peer-to-peer energy exchange among various entities including grid and Electric Vehicles (EVs). The surplus energy stored in EVs is proposed to meet the increasing demands and reduce burden on grid through Vehicle-to-Grid (V2G) technology. However, the supply from EVs may not completely meet the rising energy demands. Meanwhile, the backup batteries of 6G base stations (BSs) can be effectively utilized to supply energy to the EVs or grid. This paper explores the concept of bidirectional Telecom-to-Grid (T2G) and Telecom-to-Vehicle (T2V) energy exchange and its integration with vehicular edge computing. The utility model of BSs and EVs for bidirectional energy trading and edge computing service is designed for efficient resource utilization. An optimization problem maximizing sum of utilities is solved by two solutions, which are Gale-Shapley (GS) matching and quantum algorithm. The theoretical bounds of time consumed in an edge computing task are also derived. The optimization solution results in less emissions through quantum approach as compared to classical GS algorithm.