A Biologically Inspired Dynamic Channel Allocation Technique in 802.11 WLANs with Multiple Access Points

Appropriate channel selection for each access point (AP) is one of the major challenges in setting up and operating densely deployed 802.11 WLANs. The aim with the channel selection is to provide efficient reuse of spectrum and therefore minimize interference and improve user experience and quality of service. In this paper we adopt biologically inspired approaches in the form of hybrid genetic algorithms and simulated annealing to solve the channel selection problem in single-hop 802.11b/g networks with multiple APs. Theoretical analysis and simulation results show that our proposed hybrid algorithm has a fast convergence rate and can achieve good performance under different signal to interference and noise ratio (SINR) conditions. The algorithms are tested and compared on different network scenarios and their performance compared in terms of statistical measures.