International Journal of Computer Network and Information Security (IJCNIS)
IJCNIS Vol. 5, No. 6, 8 May 2013
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Location Prediction of Mobility Management Using Soft Computing Techniques in Cellular Network
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Author(s)
Smita Parija
1,*
Santosh Kumar Nanda
2
Prasanna Kumar Sahu
1
Sudhansu Sekhar Singh
3
Index Terms
Cellular Network, Mobility Management, Neural Network, Multi layer perceptron
Abstract
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.
Cite This Paper
Smita Parija, Santosh Kumar Nanda, Prasanna Kumar Sahu, Sudhansu Sekhar Singh, "Location Prediction of Mobility Management Using Soft Computing Techniques in Cellular Network", International Journal of Computer Network and Information Security(IJCNIS), vol.5, no.6, pp.27-33, 2013. DOI:10.5815/ijcnis.2013.06.04
Reference
[1]I.F. Akyildiz, W. Wang, The predictive user mobility profile framework for wireless multimedia networks, IEEE/ACM Transactions on Networking 12 (6) ,pp. 1021–1035,2004 doi>10.1109/TNET.2004.838604
[2]Sunan N Huang., K. K. Tan and T. H. Lee, "Further results on adaptive control for a class of nonlinear systems using neural networks," IEEE Trans. on Neural Networks, vol. 14, no. 3, pp. 719-722, 2003. D O .I:10.1109/TNN.2003.811712
[3]Naira Hovakimyan, Flavio Nardi, Anthony Calise, and Nakwan Kim, "Adaptive output feedback control of uncertain nonlinear systems using single-hidden-layer neural networks," IEEE Trans. on Neural Networks, vol. 13, no. 6, pp. 1420-1431, 2002. DOI: 10.1109/TNN.2002.804289
[4]L.P. Araujo, J.R.B. de Marca, A comparative analysis of paging and location update strategies for PCS networks, in: IEEE ICC_98, June, 1998, pp. 1390–1394. D O I: 10.1109/ICC.1998.683055
[5]A. Bhattacharya, S.K. Das, and LeZi-update: an information theoretic approach to track mobile users in PCS networks, in: ACM/IEEE MobiCom_99, August, 1999, pp. 1–12. doi>10.1145/313451.313457
[6]Y. Fang, I. Chlamtac, Y.-B. Lin, Portable movement modelling for PCS networks, IEEE Transactions on Vehicular Technology 49 (4) (2000).
[7]J. Korhonen, Introduction to 3G Mobile Communications, Artech House, Boston, MA, 2003.
[8]T. Liu, P. Bahl, I. Chlamtac, Mobility modelling, location tracking, and trajectory prediction in wireless ATM networks, IEEE Journal on Selected Areas in Communications (JSAC) 16 (6) (1998) 389–400. D O. I. 10.1109/49.709453
[9]S. Mishra, O.K. Tonguz, New metric for analyzing multistep paging schemes in mobile networks, in: IEEE VTC 2001, vol. 4, May, 2001, pp. 2590–2594. D.O I: 10.1109/VETECS.2001.944069
[10]A. Misra, A. Roy, S.K. Das, An information -theoretic framework for optimal location tracking in multi-system 4G wireless networks, in: Proceedings of IEEE INFOCOM _2004, June, 2004.
[11]Z. Naor, H. Levy. Minimizing the wireless cost of tracking mobile users: an adaptive threshold scheme, in: IEEE INFOCOM_98, March, 1998, pp. 720–727. D O.I: 10.1109/INFCOM.1998.665094
[12]A.-C. Pang, Y.-B. Lin, H.-M. Tsai, P. Agarwal, Serving radio network controller relocation for umts all-ip networks, IEEE Journal on Selected Areas in Communications 22 (4) (2004) 617–629. D O I: 10.1109/JSAC.2004.825962
[13]Guez Allon, James L. Ellbert and Moshe Kam, "Neural networks architecture for control," IEEE Control System magazine, pp. 22-25, 1998. DOI:10.1109/37.1869
[14]Rivals Isabelle and Léon Personnaz, "Nonlinear internal model control using neural networks: Application to processes with delay and design issues," IEEE Trans. on Neural Networks, vol. 11, no.1, pp. 80-90, 2000. DOI:10.1109/72.822512
[15]Yu Wen and Li Xiaoou, "Some new results on system identification with dynamic neural networks," IEEE Transactions on Neural Networks, vol.12, no. 2, pp. 412-417, 2001. DOI:10.1109/72.914535
[16]Santosh Kumar Nanda, Debi Prasad Tripathy, and Sarat Kumar Patra. "A soft computing system for opencast mining machineries noise prediction." Noise Control Engineering Journal, Vol. 59, no. 5, pp 432-446, 2011. DOI: http://dx.doi.org/10.3397/1.3614042