Chaotic Grey Wolf Optimization-based resource allocation for Vehicle-to-Everything communications

摘要

Device-to-device (D2D) enables direct communication between Vehicle-to-Everything (V2X) devices. For V2X communications, efficient power control and radio sub-channel allocation schemes are expected to accommodate the growing demand for data traffic of the increasing number of vehicular devices. We propose to investigate the resource allocation problem for V2X networks. We categorize vehicle user equipment (VUEs) into safety and non-safety VUEs and cellular user equipment (CUEs) into real-time and non-real-time CUEs according to their communication types. The objective of the proposed model is to maximize the total throughput of the system while maintaining quality of service (QoS) for CUEs and VUEs. Chaotic Grey Wolf Optimization (CGWO) algorithm, a meta-heuristic and evolutionary algorithm, is used to solve the resource allocation problem in V2X communications. Finally, comparisons between the proposed scheme and two other meta-heuristic algorithms, namely, Particle Swarm Optimization (PSO) and GWO for resource allocation, are carried out. The simulation results prove the effectiveness and performance of the proposed scheme in terms of resource allocation for V2X. They also demonstrate that CGWO-based resource allocation scheme outperforms both PSO-based and GWO-based resource allocation schemes in terms of total achieved throughput.