Congestion control strategy of VANET channel based on load prediction - Yang Ge; Zhu Yonghao (Dianzi Jishu Yingyong, 2022)
In the VANET, excessively high vehicle density will cause channel congestion, and the occurrence of channel congestion will seriously affect the performance of the cooperative vehicle safety system. Aiming at this problem, a C2SLP congestion control strategy based on the prediction of vehicle network channel load is designed. The strategy is divided into three steps. Firstly, use the detection function in the carrier-sensing multiple access protocol to obtain the busy and busy status of the channel, and perform load evaluation according to the proportion of the busy time of the channel. Then the obtained results are substituted into the autoregressive moving average model to predict the next channel load value at the moment. Finally the obtained load prediction value is compared with the preset standard value, and the power control algorithm is used to adjust the transmission power according to the comparison result to avoid channel congestion in advance. The simulation experiment results show that this strategy can stabilize the channel occupancy at about 0.6 and the transmission delay at about 30 ms. Compared with the UBRCC algorithm，this strategy can effectively reduce the transmission delay while controlling channel congestion, ensure the reliable transmission of data packets, and meet the requirements of vehicle safety applications.