Hopfield Neural Network based Dynamic Call Admission Control for Quality of Service Provisioning in Mobile Multimedia Networks

In mobile multimedia communication systems, the channel allocation schemes and computational model are becoming the topic of research interest. The computational model gives the faster processing time based on learning algorithm and neural network models. In wireless network the limited bandwidth is an issue of serious concern. However for the better utilization of available resources in a network, channel allocation scheme plays an important role to manage the available resources in each cell of cellular network. Therefore this issue should be managed to reduce the call blocking or dropping probabilities. This paper gives the new dynamic channel allocation scheme and extends the previous work, which is based on traffic mobility using Hopfield neural network.This neural network method develops the new energy function that allocates channel not only for new call but also for handoff calls on the basis of traffic mobility information. Moreover, we have also examined the performance of traffic mobility to enhance the overall Quality of Services (QoS) in terms of continuous service availability, inter-cell handoff calls and increasing traffic load.The prime objective of this paper is to decrease the handoff call dropping and blocking probability as compared to the other existing systems of static and dynamic channel allocation schemes.