Statistical Beaconing Congestion Control for Vehicular Networks

Cooperative intervehicular applications rely on the periodic exchange of broadcast single-hop status messages among vehicles, which are called beacons. The aggregated load on a wireless channel due to beacons can prevent the transmission of other types of messages, which is called channel congestion due to beaconing activity. In this paper, we propose a novel statistical approach to transmit power control (TPC) for beaconing congestion control, which is called statistical beaconing congestion control (SBCC). Unlike previous proposals, SBCC uses local information and very limited feedback, and its implementation is simple. Each vehicle locally computes the power needed to comply with a given maximum beacon load as a function of estimated channel parameters, vehicle density, and beaconing rate. A realistic Nakagami- m fading and path-loss propagation model is assumed. We provide a final expression of the algorithm as a linear proportional controller, with two variants, i.e., channel-busy-time-(CBT) based SBCC (SBCC-C) and neighbor-based SBCC (SBCC-N), depending on how the parameters are estimated. Additionally, we derive an expression for the estimated communication range under interference, which approximates the average fraction of packets lost due to hidden-node collisions. Finally, we evaluate the performance degradation caused by differences in local vehicle densities and propose a mechanism, which is called edge correction (EC), to limit it while keeping the safety benefits of an extended range at the edge of a cluster of vehicles. SBCC is validated with a realistic hybrid network-traffic simulator, and results show that it effectively controls beaconing congestion.

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