Efficient PSO Coupled with a Local Search Heuristic for Radio Resource Allocation in V2X Communications

Research on cooperative intelligent traffic issues has enhanced ground transportation's efficiency, safety, and comfort. The present work is interested in the resource allocation problem in V2X communications. We propose a new hybrid metaheuristic for a resource allocation scheme to maximize the system's total sum rate. This method is based on the particle swarm optimization (PSO) algorithm and a new suggested local search. We try to leverage the strengths and mitigate the weaknesses of both algorithms. The standard PSO algorithm has issues converging to optimal solutions because it lacks exploitation abilities. The local search aims to expand the search space vertically, allowing for a more balanced approach and addressing global exploration and local exploitation. We compared the proposed approach to the PSO and the Ant Colony Optimization (ACO) algorithms. The simulation was conducted using the MATLAB software platform. The results demonstrate that The algorithms proposed in this article significantly improve the system throughput and access rate of vehicular user equipment (VUEs) while ensuring the data rate of cellular user equipment (CUEs).'The results demonstrate the superiority of the proposed scheme.