IEEE 802.11 wireless local area networks (WLANs) have been widely deployed to provide ubiquitous broadband Internet access for wireless users. Users are often covered by multiple access points (APs) in today’s WLAN deployment. User association control is to assign or associate users in the overlapping regions to one of the APs for service. The default implementation always associates a user to the best signal AP. This leads to unsatisfactory throughput performance at congested APs and channel under-utilization at others. The performance of WLANs is highly related to user association.

We first study the joint user association and random access control optimization problem. Random access control is to determine APs’ contention windows and hence transmit probabilities, which is af...[ Read more ]

IEEE 802.11 wireless local area networks (WLANs) have been widely deployed to provide ubiquitous broadband Internet access for wireless users. Users are often covered by multiple access points (APs) in today’s WLAN deployment. User association control is to assign or associate users in the overlapping regions to one of the APs for service. The default implementation always associates a user to the best signal AP. This leads to unsatisfactory throughput performance at congested APs and channel under-utilization at others. The performance of WLANs is highly related to user association.

We first study the joint user association and random access control optimization problem. Random access control is to determine APs’ contention windows and hence transmit probabilities, which is affected by users associated with it. We propose a distributed algorithm termed CARA (Joint Client Association and Random Access Control) to tackle the problem, which iteratively optimizes user association and random access control with optimality guarantee. Through extensive simulation and experiment, we show that CARA achieves substantially higher throughput than the state-of-the-art schemes.

Secondly, we generalize our study to WLANs with coordinated beamforming (CB) capabilities. CB has emerged as a promising interference coordination approach for cooperative multiple-input-multiple-output (MIMO) systems. CB allows interfering APs to transmit as a group. Due to heavy channel state information (CSI) feedback overhead, APs need to be partitioned into cooperation groups no larger than a certain size where only APs in the same group are able to cooperate with CB. We study the novel optimization problem of minimizing AP load by joint AP grouping and user association as they are coupled. Based on alternating direction optimization, we propose DAGA (Distributed Joint AP Grouping and User Association) to tackle the optimization problem. DAGA produces an approximated user association solution which is at most e log m (m is the number of APs) times of the optimum.

Finally, we consider user migration (re-association) cost. To effect user association optimization, a user needs to handshake with the target AP for authentication and association. Therefore, there is a certain migration cost, because of the traffic and management overhead. We study the user association problem for WLANs with migration cost constraint and propose a factor-4 approximation algorithm to tackle the problem, which achieves similar performance as previous schemes but incurs much less user migration cost.