Abstract
Dynamic Channel Allocation (DCA) schemes based on Artificial Neural Network (ANN) technology were seen as performing better overall than conventional statistically based Channel Allocation!DCA Channel Allocation!DCA Channel Allocation!DCA Channel Allocation!DCA DCA schemes. Furthermore, some papers report that within the ANN schemes adopted as Channel Allocators (CA), the Neural Network!HNN Neural Network!HNN Neural Network!HNN Neural Network!HNN Neural Network!Hopfield Neural Network!Hopfield Neural Network!Hopfield Neural Network!Hopfield Hopfield Neural Network (HNN) performs considerably better than the conventional non-Neural Network!HNN HNN methods. The work reported in this paper is a summary of research where a new HNNCA is proposed and simulated to check the validity of the argument itself. The simulation of the project was done through non-uniform traffic to simulate extreme conditions and have a more realistic approach; the number of prerecorded patterns was also a subject of the simulation. The simulation’s results recorded different correlated situations and there have been substantial conclusions that can be made from the simulation itself.
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