Proportional fairness in multi-rate wireless LANs

In multi-rate wireless LANs, throughput-based fair bandwidth allocation can lead to drastically reduced aggregate throughput. To balance aggregate throughput while serving users in a fair manner, proportional fair or time-based fair scheduling has been proposed to apply at each access point (AP). However, since a realistic deployment of wireless LANs can consist of it network of APs, this paper considers proportional fairness in this much wider setting. Our technique is to intelligently associate users with APs to achieve optimal proportional fairness in a network of APs. We propose two approximation algorithms For periodical offline optimization. Our algorithms are the first approximation algorithms in the literature with tight worst-case guarantee for the NP-hard problem. Our tight simulation results demonstrate that our algorithms can obtain an aggregate throughput which can he as much as 2.3 times more than that of the max-min fair allocation in 802.11b. While maintaining aggregate throughput, our approximation, algorithms outperform the default user-AP association method in the 802.11b standard significantly in terms of fairness.