Jain’s Fairness Index Optimization in RIS-Assisted UAV V2X Systems Based on MASAC

This paper investigates a land-air integrated vehicular network (V2X) system comprising heterogeneous communication links, including vehicle-to-vehicle (V2V) links, base station-reconfigurable intelligent surface-vehicle (BS-RIS-V) links, and unmanned aerial vehicle (UAV0-UAV) links. To ensure fairness in resource allocation, we first establish transmission rate models for each communication link. We then formulate an optimization problem aimed at maximizing Jain’s fairness index (J), subject to constraints on transmission power, bandwidth, and IRS configuration. To tackle this challenging non-convex problem, we develop a Multi-Agent Soft Actor-Critic (MASAC) algorithm tailored for joint resource optimization. Simulation results validate the effectiveness of the proposed approach, showing significant improvements in both fairness and system throughput. Compared to baseline methods, our algorithm achieves a more balanced resource distribution while maintaining high overall performance.