一种车联网自适应功率控制策略

Adaptive Power Control Strategy for VANET

信道拥塞会导致数据包碰撞和丢失,使安全相关的消息无法可靠发送.而传统的信道拥塞控制通过检测信道占有率、信噪比和当前时刻节点数目,对功率进行被动控制,且大部分算法是开环控制,具有滞后性和不精确性.针对传统功率控制的滞后性和不精确性,基于模糊逻辑提出一种车联网自适应功率控制策略FAPCS(Adaptive Power Control Strategy Based On Fuzzy Logic).首先,建立了传输范围预测模型,通过预测交通流密度值,预测出满足90%数据包递送率的传输范围;然后,针对隐藏终端和预测密度的误差对数据包递送率的影响,设计了传输范围自适应调整模型,该模型通过模糊逻辑推理,得到满足90%数据包递送率的真实传输范围.仿真结果表明,该控制策略能够避免信道拥塞,使数据包递送率满足安全相关应用的需要,且具有较快收敛速度.

Channel congestion would lead to a significant amount of packets collisions and losses. Therefore, vehicles cannot receive the safety-related information from their neighboring nodes. Traditional congestion control schemes rely on the measured channel occupan- cy rate, signal-to-noise ratio and the number of neighboring nodes to passively adjust the transmission power. These existing congestion control schemes adjust the transmission power in a open-loop manner and have the limits of lagging and imprecision. In this paper, an adaptive power control strategy for VANET based on fuzzy logic （ FAPCS ） is proposed. Firstly, a model that predicts transmission range is designed. This model is used to predict an ideal transmission range that achieves the PDR of 90% based on the estimated vehi- cle density. Then ,in order to mitigate the effects of hidden nodes and the errors in estimating the vehicle density, an adaptive transmis- sion range control model is proposed. The model generates the real transmission range that achieve the PDR of 90% using the fuzzy logic reasoning technique. Simulation results show that the proposed adaptive power controller has faster convergence performance and can avoid the channel congestion and meet the requirements of safety-related applications in vehicular networks.