Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Swarm intelligence: from natural to artificial systems
Swarm intelligence: from natural to artificial systems
Optimization of AP Placement and Channel Assignment in Wireless LANs
LCN '02 Proceedings of the 27th Annual IEEE Conference on Local Computer Networks
Large-scale wireless LAN design
IEEE Communications Magazine
Quality-of-service in ad hoc carrier sense multiple access wireless networks
IEEE Journal on Selected Areas in Communications
Performance model for IEEE 802.11s wireless mesh network deployment design
Journal of Parallel and Distributed Computing
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Frequency optimization is required to maximize the WLAN throughput in environments where several networks coexist. This paper evaluates four throughput estimation models and two optimization algorithms. Throughput is selected as the optimization criteria for channel assignment. Thus, the result of a throughput estimation model is used as an input for an optimization algorithm. The target is a frequency plan that maximizes multi-cell WLAN throughput. The throughput estimation models are based on radio spectrum usage, practical throughput measurements, WLAN protocol behavior, and theoretical coverage estimations. The models use separate functions for defining the minimum channel distance. In the evaluation, Genetic Algorithm (GA) and a distributed optimization algorithm produce the final frequency plan. A dedicated simulator has been implemented for the evaluation. As overall results, the evaluated throughput estimation models did not produce significant WLAN throughput improvements compared to each other. Still, the selection of the throughput estimation model and optimization algorithm pair is significant for results, since certain combinations cause poor results.