Cellular channel assignment using transient chaotic neural network with self-organizing pattern formation initializing

The channel assignment problems (CAP) in a cellular mobile network have become increasingly important because of limited usable range of the frequency spectrum. In this paper, a new efficient self-organizing channel assignment algorithm combined transiently chaotic neural network (TCNN) is proposed. The efficiency of the algorithm is verified through solving the well-known Sivarajan and Kunz´s benchmark problems with non-interference solutions, while the iteration numbers is comparable with state-of-the-art algorithms