Abstract
In a Wireless Local Area Network (WLAN), clients typically associate with the AP that offers the maximal signal strength. Later works on client-AP association then further take load balancing and fairness into consideration. Those schemes however are not directly applicable in a multiuser MIMO (MU-MIMO) WLAN since different combinations of clients result in different throughput of each individual client. We show that the AP association problem for maximizing sum rate (the summation of all clients’ data rates) in multi-cell MU-MIMO downlink networks is NP-hard. Therefore, in this thesis, we present two client AP association algorithm customized for MU-MIMO WLANs. The proposed algorithm jointly solves the problems of client-AP association and MU-MIMO client grouping with consideration of channel correlation among clients. It hence allows a good group of clients, i.e., those with low channel correlation, to together associate with the same proper AP and achieve a high sum-rate. The first algorithm makes a client select an proper AP based on sum rate, and the second algorithm dynamically makes some clients associate with different APs for adapting various network conditions (e.g., the change of channel quality, client joining and leaving due to mobility). For practical use, we further extend the second algorithm to a distributed scheme. The simulation results show that our MU-MIMO AP association algorithm improves the aggregate throughput by about 11%-28% and 26%-45%, as compared to two common association approaches, i.e., RSSI-based and load-based schemes, respectively.