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-carrier-M-segment FAP problem, we construct a TCNN consisting of NxM 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.

[1]  L. Chua,et al.  A universal circuit for studying and generating chaos. I. Routes to chaos , 1993 .

[2]  S. H. Huang,et al.  Artificial neural networks in manufacturing: concepts, applications, and perspectives , 1994 .

[3]  M.C. Jeruchim,et al.  A survey of interference problems and applications to geostationary satellite networks , 1977, Proceedings of the IEEE.

[4]  Panos M. Pardalos,et al.  Frequency Assignment Problems , 1999, Handbook of Combinatorial Optimization.

[5]  H.E. Rauch,et al.  Neural networks for routing communication traffic , 1988, IEEE Control Systems Magazine.

[6]  Lipo Wang,et al.  A noisy chaotic neural network for solving combinatorial optimization problems: stochastic chaotic simulated annealing , 2004, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[7]  Kate Smith-Miles,et al.  On chaotic simulated annealing , 1998, IEEE Trans. Neural Networks.

[8]  Sancho Salcedo-Sanz,et al.  A Hybrid Neural-Genetic Algorithm for the Frequency Assignment Problem in Satellite Communications , 2005, Applied Intelligence.

[9]  Ángel Rodríguez-Vázquez,et al.  Integrated chaos generators , 2002 .

[10]  Kazuyuki Aihara,et al.  Chaos engineering and its application to parallel distributed processing with chaotic neural networks , 2002, Proc. IEEE.

[11]  Henry Leung,et al.  A study of the transiently chaotic neural network for combinatorial optimization , 2002 .

[12]  Hiroshi Nozawa,et al.  A neural network model as a globally coupled map and applications based on chaos. , 1992, Chaos.

[13]  Lipo Wang,et al.  Multi-associative neural networks and their applications to learning and retrieving complex spatio-temporal sequences , 1999, IEEE Trans. Syst. Man Cybern. Part B.

[14]  H. Nozawa,et al.  Solution of the optimization problem using the neural network model as a globally coupled map , 1994 .

[15]  Nobuo Funabiki,et al.  A gradual neural-network approach for frequency assignment in satellite communication systems , 1997, IEEE Trans. Neural Networks.

[16]  J J Hopfield,et al.  Neurons with graded response have collective computational properties like those of two-state neurons. , 1984, Proceedings of the National Academy of Sciences of the United States of America.

[17]  Takeshi Mizuike,et al.  Optimization of frequency assignment , 1989, IEEE Trans. Commun..

[18]  Kazuyuki Aihara,et al.  Chaotic simulated annealing by a neural network model with transient chaos , 1995, Neural Networks.

[19]  J J Hopfield,et al.  Neural networks and physical systems with emergent collective computational abilities. , 1982, Proceedings of the National Academy of Sciences of the United States of America.

[20]  Kazuyuki Aihara,et al.  Adaptive annealing for chaotic optimization , 1996 .

[21]  Simon Haykin,et al.  Neural Networks: A Comprehensive Foundation , 1998 .

[22]  B. Pontano,et al.  Interference into Angle-Modulated Systems Carrying Multichannel Telephony Signals , 1973, IEEE Trans. Commun..

[23]  C. Wu,et al.  A Universal Circuit for Studying and Generating Chaos-Part I: Routes , 1993 .

[24]  Sancho Salcedo-Sanz,et al.  A hybrid Hopfield network-simulated annealing approach for frequency assignment in satellite communications systems , 2004, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[25]  Jiahai Wang,et al.  A method to improve the transiently chaotic neural network , 2004, Neurocomputing.

[26]  Yuyao He,et al.  Chaotic simulated annealing with decaying chaotic noise , 2002, IEEE Trans. Neural Networks.

[27]  S. Sharma,et al.  An exploratory study of chaos in human-Machine system dynamics , 2006, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.