An immune inspired approach to 802.11 Wireless LANs coverage optimization

Coverage optimization is a critical issue in 802.11 Wireless LANs planning problems. In this paper an immune network algorithm named opt-aiNet is studied in order to automatize the planning process by optimizing the BS´s (Base Station) sites. Compared the results of opt-aiNet and genetic algorithms(GA) which have been used in radio coverage optimization before, we found that opt-aiNet could find the optimal solution all times while GA falling into local optimum solution sometimes, and opt-aiNet converged more quickly than GA in most cases. Experimental results show that opt-aiNet is an effective way to optimize the 802.11 Wireless LANs planning problems.