Minimizing interference in satellite communications using transiently chaotic neural networks

The frequency assignment problem (FAP) in satellite communications is solved with transiently chaotic neural networks (TCNN). The objective of this optimization problem is to minimize cochannel interference between two satellite systems by rearranging the frequency assignments. For an NN-carrier–MM-segment FAP problem, we construct a TCNN consisting of N×MN×M neurons. The performance of the TCNN is demonstrated through solving a set of benchmark problems, where the TCNN finds comparative if not better solutions as compared to the existing algorithms.