Joint Vehicle Pairing, Spectrum Assignment, and Power Control for Sum-Rate Maximization in NOMA-Based V2X Underlaid Cellular Networks

Abstract

Vehicle-to-everything (V2X) underlaid cellular networks in underlaid mode suffer catastrophic co-channel interference caused by spectrum sharing, results in a reduced system sum-rate. To cope with this, this work studies a social-mobility-aware nonorthogonal multiple access (NOMA)-enabled V2X underlaid cellular network to mitigate the co-channel interference and improve the sum rate. By jointly optimizing vehicle pairing and resources, a sum-rate maximization problem is formulated under the diverse quality of service requirements of both cellular and vehicular users. The formulated problem is proved to be a nondeterministic polynomial-time (NP)-hard problem and is difficult to solve. As an alternative, we propose a NOMA-based joint vehicle pairing, spectrum assignment, and power control algorithm (NOMA-JVP-SA-PCA), with which the original problem is decomposed into two disjoint subproblems, i.e., 1) joint vehicle pairing and spectrum assignment subproblem and 2) power control subproblem. Dealing the first subproblem, we propose a heuristic social-mobility-aware vehicle pairing algorithm (HSMA-VPA) and a revised Kuhn-Munkres-based spectrum assignment algorithm (KM-SAA) to acquire the vehicle pairing and spectrum assignment solutions. Then, solving the second subproblem, a closed-form power solution is obtained utilizing a 3-D geometric power control approach (3D-PCA). Finally, we solve the original problem through an iterative method. Simulation results show that the proposed NOMA-JVP-SA-PCA effectively enhances the sum rate and outperforms the baseline algorithms around 24%–53% within a specific range.