Energy-Efficient Resource Allocation for Parked-Cars-Based Cellular-V2V Heterogeneous Networks

As the fast development of vehicular network, the layout of the roadside unit (RSU) is indispensable. Due to the shackles of factors, such as coverage and cost, there is an urgent need for effective solution to solve the contradiction that RSU cannot be deployed on large scale. Parked cars provide a feasible solution for replacing RSUs and effectively reducing the arrangement of edge nodes. Inspired by this, parked cars as RSUs (P-RSUs) are leveraged to support cities' vehicular network in this article. We first construct the P-RSU-based cellular-V2V heterogeneous networks (C-V2V HetNets) system model, and then formulate an optimization problem to maximize the energy efficiency (EE) of C-V2V HetNets with parked cars. Since the proposed issue is an NP-hard mixed-integer nonlinear programming (MINLP) problem coupled with P-RSU incentive, we reformulate it into two subproblems, which are the P-RSU recruitment and the joint resource allocation. For the first subproblem, an effective reverse auction-based mechanism is given to encourage parked cars participate and become P-RSUs. For the second subproblem, nonlinear fractional programming is used to optimize transmission power, and many-to-one matching is utilized to effectively obtain channel reusing scheme constrained by QoS. Moreover, a multihop-based transmission strategy is given to further expand vehicular network coverage. Algorithms are evaluated based on real-world scenarios using SUMO. Numerical results demonstrate that the proposed approach can both effectively recruit P-RSUs with low cost and achieve excellent system performance in terms of EE, spectrum efficiency, and network coverage compared to other benchmark algorithms.