Self-organizing maps
Mobile Cellular Telecommunications Systems
Mobile Cellular Telecommunications Systems
Channel assignment schemes for cellular mobile telecommunication systems: A comprehensive survey
IEEE Communications Surveys & Tutorials
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Static and dynamic channel assignment using neural networks
IEEE Journal on Selected Areas in Communications
Borrowing channel assignment strategies based on heuristic techniques for cellular systems
IEEE Transactions on Neural Networks
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The fast growing cellular mobile systems demand more efficient and faster channel allocation techniques. Borrowing channel assignment (BCA) is a compromising technique between fixed channel allocation (FCA) and dynamic channel allocation (DCA). However, in the case of patterned traffic load, BCA is not efficient to further enhance the performance because some heavy-traffic cells are unable to borrow channels from neighboring cells that do not have unused nominal channels. The performance of the whole system can be raised if the short-term traffic load can be predicted and the nominal channels can be re-assigned for all cells. This paper describes an improved BCA scheme using traffic load prediction. The prediction is obtained by using the short-term forecasting ability of cellular probabilistic self-organizing map (CPSOM). This paper shows that the proposed CPSOM-based BCA method is able to enhance the performance of patterned traffic load compared with the traditional BCA methods. Simulation results corroborate that the proposed method delivers significantly better performance than BCA for patterned traffic load situations, and is virtually as good as BCA in the other situations analyzed.