Sensitivity-driven Adaptive Contention Window Optimization for IEEE 802.11 based V2I Networks

Abstract

In vehicle-to-infrastructure (V2I) communication the setting of IEEE 802.11 Distributed Coordination Function (DCF) parameters has a decisive bearing on performance, yet the literature seldom pins down how much each parameter actually matters once traffic, MAC and queueing are modelled together. Treating a previously validated analytical framework as a fixed deterministic input-output map, we rank the DCF and traffic parameters that shape throughput, collision probability, delay, packet delivery ratio and Age of Information in a single-AP V2I network. A local one-factor-at-a-time analysis, cast in dimensionless elasticities so that parameters of different units become comparable, is paired with a variance-based global analysis built on first-order and total-effect Sobol indices. Two clean groups emerge: collision probability is set by the contending-vehicle population -- itself governed by vehicle velocity and density -- together with the minimum contention window, whereas delay is driven by the channel rate, the offered load and the packet size, and carries strong interaction effects that no local reading can expose. We then derive the closed-form structure of these sensitivities from the model relations, which explains the rankings, forces certain parameters into equal-magnitude elasticities, and locates where the local ranking reverses. Finally the collision-sensitivity structure is turned into a design output rather than a ranking: a closed-form contention-window control law, linear in the contending population and closed with a Greenshields density model, that a roadside access point can evaluate online from measured density or velocity. The fixed IEEE 802.11 default is recovered as the single population at which this law is optimal; away from it the throughput gain grows with density and is largest in the dense, safety-critical regime.