Access-rate enhancement for underlay many-to-many vehicular communications: QoS-aware resource sharing and power control

In urban vehicle-to-vehicle (V2V) networks, a high access rate is essential to meet elevated connectivity demands and ensure wide service coverage. Existing resource-allocation strategies often trade off user coverage for throughput, or fail to ensure quality-of-service (QoS) under aggressive channel reuse. To overcome these limitations, we present a lexicographic two-phase resource allocation framework that decouples access-rate enhancement from sum rate optimization. Phase I employs many-to-many channel reuse, exact-power provisioning, and capacity-aware rate-splitting to admit the maximum feasible set of V2V links under strict signal-to-interference-plus-noise ratio (SINR) and QoS constraints. Phase II applies a Genetic Algorithm (GA) to optimize transmit powers over the channel allocations and minimum data-rate guarantees established in Phase I, maximizing overall sum rate without altering the admitted link set. Simulation results demonstrate that our approach significantly outperforms benchmark resource allocation methods in both access rate and sum rate, particularly in interference-constrained urban scenarios.