Research On Adaptive Channel Congestion Control Strategy For DSRC/WAVE

Collaborative security applications are the most forward-looking and challenging applications in VAENT. It is used to conduct security warning and location tracking by sharing the wireless channel between V2V and V2I in mutual perception and interaction. However, due to the influence of dynamic changes in vehicle topology, frequent changes in vehicle density, terrain and other vehicles for wireless communication process, it will lead to a serious decline in the performance of wireless communication, and resulted in data packet delivery rate decreased, transmission delay increased, threatened the driver’s life and property safety. Therefore, it is necessary to design a control strategy to avoid channel congestion, so that the packet delivery rate and message latency can meet the requirements.We discuss the key technologies of cooperative security applications, and analyze the challenges which collaborative security applications faced, and study the impact of the channel congestion on DSRC wireless communication process. Two kinds of congestion avoidance method are proposed. (1) In view of the influence of the traffic flow density change for the channel congestion, the lag and the inaccuracy of the traditional congestion control strategy, an adaptive power control strategy based on fuzzy logic (FAPCS) is proposed. First, we build the prediction model of the transmission range by predicting traffic density to forecast the transmission range of meeting the packet delivery rate up to 90%.Then, we design the adaptive adjustment model based on fuzzy feedback inference technology to solve the impact of hidden terminal and density prediction error on packet delivery ratio, and to get the real transmission range of the packet deliver rate up to 90%. (2) Because the present collaborative security applications generally do not consider microscopic characteristics of the vehicle and application requirements, an adaptive rate control method based on channel congestion price is proposed, the method can realize on-demand allocation of transmission rate according to the vehicle to the neighbor node running state, to ensure network utility maximization. First, communication interference model to perceive the communication environment is established, and channel capacity is gotten. Then, we establish utility function between the relative relationships of the vehicle nodes and the transmission rate, to calculate the physical layer transmission rate. Finally, we establish the channel congestion price model through the mismatch of transmission rate and queue length, to adaptively adjust the message generation rate in next time.The two methods to improve collaborative safety application’s performance are validated by simulation experiments. Simulation results show that the adaptive power control strategy based on fuzzy logic can avoid channel congestion, make channel utilization is less than 70%, with a faster convergence rate that guarantee the reliability of broadcasting. The adaptive rate control strategy based on the vehicle running environment awareness uses utility function to ensure the on-demand allocation of communication resources, and uses the predicting technology to avoid channel congestion, and to adaptively adjust the message generation rate by using exponential function, significantly reduce the message transmission delay and guarantee real-time broadcast.