WLAN中基于信道预测的自动速率选择机制研究

提出了采用线性AR模型信道预测技术来提高IEEE 802.11中自动速率选择机制性能的方法,克服了检测RSS和发送数据帧之间的时间差影响.在发送端,根据历史接收帧的RSS值来估计当前帧发送时接收端的RSS水平,并结合发送帧长度和帧重传数来进行最佳发送速率的选择.对AR模型预测算法的步长选择进行了分析,在NS2网络仿真软件的TwoRayGround和Ricean信道模型下进行了仿真.仿真结果表明此机制比无预测机制提高了7%~30%的平均吞吐量水平.

An Auto Rate Selection Mechanism Based on Channel Prediction for Wireless LAN

A linear auto regressive (AR) model channel prediction technique is proposed to enhance the performance of auto rate selection mechanism in IEEE 802.11, and eliminate the delay effect between measurement of received signal strength (RSS) values and rate selection for the immediate frame transmission. The best rate is selected based on the data payload length, frame retry count and the RSS value estimated from recorded values. The estimation step-size is analyzed and the proposed mechanism is simulated in TwoRayGround and Ricean channel models in the NS2 environment. Simulation results show that the proposed mechanism enhances mean throughput performance of IEEE 802.11 system compared with that presented in the literature. In saturation, the enhancement reaches 7%, and under a finite load condition, the enhancement reaches 30%.