Dynamic Frequency Self-Optimization For Dense Wlans

Frequency optimization has a great impact on lots of network Key Performance Indicators (KPIs). Conventional approaches focus on direct mitigating contention or interference among Access Points (APs), ignoring the network KPIs and their conflicts. In this paper, we propose a novel Frequency Self-Optimization (FSO) scheme to improve network KPIs in dense Wireless Local Area Networks (WLANs) where network environment is highly dynamic. By modeling the network load and related KPIs, we can derive an optimal frequency assignment solution for all APs. We formulate this problem as a multi-objective optimization problem and propose an Evolutionary Particle Swarm Optimization (EPSO) algorithm to reduce the user dissatisfaction degree and service interruption ratio, and improve the network throughput as well. Simulation results show that the proposed scheme greatly improves network KPIs and outperforms the traditional ones e.g. Dynamic access point Load-based Plan (DYLD) scheme.