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 N N -carrierM M -segment FAP problem, we construct a TCNN consisting of NM N  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.
satellite communications neural network fap optimization