Location Prediction of Mobility Management Using Soft Computing Techniques in Cellular Network

Автор: Smita Parija, Santosh Kumar Nanda, Prasanna Kumar Sahu, Sudhansu Sekhar Singh

Журнал: International Journal of Computer Network and Information Security(IJCNIS) @ijcnis

Статья в выпуске: 6 vol.5, 2013 года.

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This work describes the neural network technique to solve location management problem. A multilayer neural model is designed to predict the future prediction of the subscriber based on the past predicted information of the subscriber. In this research work, a prediction based location management scheme is proposed for locating a mobile terminal in a communication without losing quality maintains a good response. There are various methods of location management schemes for prediction of the mobile user. Based on individual characteristic of the user, prediction based location management can be implemented. This work is purely analytical which need the past movement of the subscriber and compared with the simulated one. The movement of the mobile target is considered as regular and uniform. An artificial neural network model is used for mobility management to reduce the total cost. Single or multiple mobile targets can be predicted. Among all the neural techniques multilayer perceptron is used for this work. The records are collected from the past movement and are used to train the network for the future prediction. The analytical result of the prediction method is found to be satisfactory.

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Cellular Network, Mobility Management, Neural Network, Multi layer perceptron

Короткий адрес: https://sciup.org/15011198

IDR: 15011198

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