Cellular channel assignment: a new localized and distributed strategy
Mobile Networks and Applications - Dial m for mobility: discrete algorithms and methods for mobile computing and communication
Cellular Radio: Analog and Digital Systems
Cellular Radio: Analog and Digital Systems
Mobile Cellular Telecommunications Systems
Mobile Cellular Telecommunications Systems
Constraint Handling in Evolutionary Search: A Case Study of the Frequency Assignment
PPSN IV Proceedings of the 4th International Conference on Parallel Problem Solving from Nature
An efficient evolutionary algorithm for channel resource managementin cellular mobile systems
IEEE Transactions on Evolutionary Computation
Static and dynamic channel assignment using neural networks
IEEE Journal on Selected Areas in Communications
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In GSM Telecommunication networks it is important to efficiently utilize the scarce radio spectrum using a proper channel assignment scheme. The objective of a Channel Assignment problem is to assign a required number of channels to each cell in a way to achieve both efficient frequency spectrum utilization and minimization of interference effects (by satisfying a number of channel reuse constraints). Dynamic Channel Assignment (DCA) assigns the channels to the cells dynamically according to traffic demand, and hence, can provide higher capacity (or lower call blocking probability), fidelity and quality of service than the fixed assignment schemes. Devising a DCA, that is practical, efficient, and which can generate high quality allocations, is challenging. This paper presents an effective and efficient Modified Genetic Algorithm (MGA) for the solution of DCA Problem.