Multiobjective optimization-based radio resource allocation and sharing algorithm for D2D-based V2V communication

Vehicular communication systems have recently attracted a lot of attention because of their potential to improve road efficiency, comfort, and safety. In this paper, we investigate the resource management problem for device-to-device-based vehicle-to-vehicle communication. A multiobjective radio resource allocation and sharing algorithm is proposed based on a swarm intelligence algorithm called ant colony optimization (ACO). First, for the resource allocation process, three objective functions are formulated to maximize the users' transmission capacity, reduce the mobile transmission power, and minimize the intracell interference. Second, for the resource sharing process, we define two objective functions to optimize the resource utilization and reduce the intercell interference. Finally, a weighted sum method is used to join these objective functions and define one multiobjective optimization problem. The ACO algorithm is used to determine the Pareto optimal solution. Simulation results show that the proposed algorithm performs well and achieves promising performance in terms of network sum rate, packet drop rate, average queuing delay, resource utilization, and mobile's transmission power.