text: The focus of this paper is on the rate and power control algorithms in Dedicated Short Range Communication (DSRC) for vehicular networks. We first propose a utility maximization framework by leveraging the well-developed network congestion control, and formulate two subproblems, one on rate control with fixed transmit powers and the other on power control with fixed rates. Distributed rate control and power control algorithms are developed to solve these two subproblems, respectively, and are proved to be asymptotically optimal. Joint rate and power control can be done by using the two algorithms in an alternating fashion. The performance enhancement of our algorithms compared with a recent rate control algorithm, called EMBARC, is evaluated by using the network simulator ns2.
  @cite_18: Abstract 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, including realistic propagation as well as environment modeling and realistic vehicle operational environments (varying demand on both awareness range and rate), we show that ECPR can increase awareness by 20 while keeping the channel load and interference at almost the same level. When permitted by the awareness requirements, ECPR can improve the average message rate by 18 compared to algorithms that perform rate adaptation only.
  @cite_7: In Vehicle Safety Communications (VSC) based on IEEE 802.11p, vehicles establish a mutual awareness of their presence by periodically broadcasting status messages, aka beacons. If vehicle density is high and beaconing is not regulated, the channel can become congested, impairing reception performance and safety benefit. As a countermeasure, a number of congestion control approaches have been suggested, adapting transmit (Tx) power, beacon generation rate (Tx rate), or both. However, in general these approaches did not show what the optimal outcome for congestion control would be and how and why their solution would lead to the desired result. In this work, we analyze answers to the first question and provide a methodology for the second. We systematically derive a joint power rate control strategy for VSC which optimizes reception performance for a targeted sender-receiver distance. We start by laying out why we consider average (or percentile of) packet Inter-Reception Time (IRT) at the targeted awareness distance to be a suitable metric for our purpose. Then, we analyze a wide range of Tx parameters to identify which combinations optimize reception in a homogeneous scenario. We show that for each sender-receiver distance, there is an optimal Tx power which, unlike the corresponding Tx rate, is independent of node density. In addition, we analyze the Pareto optimal Tx parameter combinations for two groups of vehicles with different target distances adapting at the same time. We show that the majority of these combinations use the same Tx power as identified in the homogeneous case. We conclude that a simple and efficient strategy to optimize reception performance is to select Tx power w.r.t. the targeted distance and to adapt Tx rate w.r.t. channel load.
  @cite_13: Vehicular ad hoc networks play a critical role in enabling important active safety applications such as cooperative collision warning. These active safety applications rely on continuous broadcast of self-information by all vehicles, which allows each vehicle to track all its neighboring cars in real time. The most pressing challenge in such safety-driven communication is to maintain acceptable tracking accuracy while avoiding congestion in the shared channel. In this article we propose a transmission control protocol that adapts communication rate and power based on the dynamics of a vehicular network and safety-driven tracking process. The proposed solution uses a closed-loop control concept and accounts for wireless channel unreliability. Simulation results confirm that if packet generation rate and associated transmission power for safety messages are adjusted in an on-demand and adaptive fashion, robust tracking is possible under various traffic conditions.
  @cite_12: Cooperative vehicle safety (CVS) systems operate based on broadcast of vehicle position and safety information to neighboring cars. The communication medium of CVS is a vehicular ad-hoc network. One of the main challenges in large scale deployment of CVS systems is the issue of scalability. To address the scalability problem, several congestion control methods have been proposed and are currently under field study. These algorithms adapt transmission rate and power based on network measures such as channel busy ratio. We examine two such algorithms and study their dynamic behavior in time and space to evaluate stability (in time) and fairness (in space) properties of these algorithms. We present stability conditions and evaluate stability and fairness of the algorithms through simulation experiments. Results show that there is a trade-off between fast convergence, temporal stability and spatial fairness. The proper ranges of parameters for achieving stability are presented for the discussed algorithms. Stability is verified for all typical highway density cases for static traffic as well as real scenarios. Fairness is shown to be naturally achieved for some algorithms and its analysis is under study in another work of us. Under the same conditions other algorithms may have problem to maintain fairness in space. We have shown that this can be resolved by a distributed measurement of CBR and is verified.
  @cite_11: Cooperative vehicle safety (CVS) systems rely on vehicular ad-hoc networks operating in broadcast mode to deliver vehicle tracking and safety information to neighboring cars. This information is used to enable collision avoidance and warning systems. One of the main challenges of the eventual large scale deployment of such systems is network congestion, which could critically degrade the quality of a CVS system. In this paper, we present a method for congestion monitoring and control based on limited feedback from the network. We study the relationship between channel occupancy, as a readily available feedback measure, controllable network parameters, and network performance. We describe a performance measure relevant to CVS systems and present a congestion control method, based on channel occupancy measurements, that robustly maintains the system performance near optimal operation points. We examine the convergence properties of the congestion control algorithm and provide guidelines for the design of such systems based on network and traffic density conditions. Through simulation experiments we show significant gains in performance when closed loop congestion control methods are applied.
summary: Other related work includes the database approach proposed in @cite_7 , where the optimal broadcast rates and transmission power are calculated offline based on the network configurations. Also, @cite_18 proposed an environment and context-aware distributed congestion control (DCC) algorithm, which jointly control the rate and power to improve cooperative awareness by adapting to both specific propagation environments (such as urban intersections, open highways, suburban roads) as well as application requirements (e.g., different target cooperative awareness range). However, the stability and convergence of the algorithm are not proved mathematically. Besides the rate control algorithm IVTRC, the authors also proposed range control algorithms in @cite_11 @cite_13 @cite_12 where the objective is to adapt the transmission ranges to achieve a specific threshold. The motivation of limiting channel loads below the threshold is to control channel congestion to maximize effective channel throughput. However, fair resource allocation among vehicles to increase the safety awareness of all vehicles are not considered, and the stability of the algorithms is subject to certain conditions @cite_12 .