Self-Learning Rate Adaptation in Multi-rate 802.11 Networks
Given the multi-rate option in most 802.11 standards, rate adaptation based on dynamic channel condition is crucial to the system performance. This paper presents an efficient self-learning rate adaptation mechanism at MAC layer, called SLRA. SLRA takes both the temporal or spatial correlation and cha- nge into account. The rate selection has two steps: one is to evaluate the performance of current rate and decide whether to adjust the rate; the second is to calib- rate the decision according to the historical experiments of rate adjustment at similar channel status. We evaluate SLRA in 802.11 network and find that it can choose the right rate at most time and performs better than other sender-side adaptation schemes.
Shaohe Lv Xiaodong Wang Xingming Zhou Chi Liu
National Laboratory for Parallel and Distributed Processing, National University of Defense Technology, Changsha, Hunan, China, 410073
国际会议
上海
英文
2007-09-21（万方平台首次上网日期，不代表论文的发表时间）