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Precise Location Prediction Algorithms Using Improved Random Walk-based and Generalized Markovian Mobility Models

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4 Author(s)
Karoly Lendvai ; Budapest University of Technology and Economics, Department of Telecommunication2, Magyar tudósok körútja, Budapest 1117, Hungary. ; Peter Fulop ; Sandor Szabo ; Tamas Szalka

The paper discusses about the precise location prediction algorithms using improved random walk-based and generalized Markovian mobility models. This algorithm is used in mobile and cellular network dimensioning, dynamic resource allocation in cells, justifying CAC decisions and QoS parameter tuning, predicting user distribution and motion drifts in network, and estimating number of users in current and adjacent cells. It presents the mobility modeling approaches, random walked model extension, proposition of a Markovian model with memory extension and accuracy measurement results. The said algorithm is most efficient in call admission control (CAC) approach or other QoS decisions.

Published in:

Telecommunications Network Strategy and Planning Symposium, 2008. Networks 2008. The 13th International

Date of Conference:

Sept. 28 2008-Oct. 2 2008