Safety and efficiency applications in vehicular networks rely on the exchange of periodic messages between vehicles. These messages contain position, speed, heading, and other vital information that makes the vehicles aware of their surroundings. The drawback of exchanging periodic cooperative messages is that they generate significant channel load. Decentralized Congestion Control (DCC) algorithms have been proposed to minimize the channel load. However, while the rationale for periodic message exchange is to improve awareness, existing DCC algorithms do not use awareness as a metric for deciding when, at what power, and at what rate the periodic messages need to be sent in order to make sure all vehicles are informed. We propose an environment-and context-aware DCC algorithm combines power and rate control in order to improve cooperative awareness by adapting to both specific propagation environments (e.g., urban intersections, open highways, suburban roads) as well as application requirements (e.g., different target cooperative awareness range). Studying various operational conditions (e.g., speed, direction, and application requirement), ECPR adjusts the transmit power of the messages in order to reach the desired awareness ratio at the target distance while at the same time controlling the channel load using an adaptive rate control algorithm. By performing extensive simulations, * Corresponding author * * M. Boban carried out this work while at NEC Laboratories Europe.
Aygun et al. REF proposed an environment-and context-aware decentralized congestion control algorithm that combines power and rate control to improve cooperative awareness by adapting to propagation environments for vehicular communications.
ECPR: Environment- and Context-aware Combined Power and Rate Distributed Congestion Control for Vehicular Communications
ArXiv
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Computer Science