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Entropy-based location management in long-term evolution cellular systems

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3 Author(s)
A. Roy ; School of Information and Communication Engineering, Sungkyunkwan University, Suwon, Republic of Korea ; J. Shin ; N. Saxena

The recently emerging location-based services in long-term evolution (LTE) systems require the accurate and efficient tracking of mobile users. An optimal information-theoretic framework is developed for tracking area update (TAU) for next-generation LTE cellular systems. Shannon's entropy is used to characterise the location uncertainty of the mobile users. Based on this entropy-based tracking framework, two practical location management schemes, Bayesian-based TAU and entropy-coding based TAU, are proposed. The proposed schemes capture the users' mobility patterns online and perform profile-based paging to optimise the TAU cost. Of the two proposed schemes, the Bayesian-based TAU operates as an independently identically distributed process and improves the paging cost with less storage and computational overhead, whereas the entropy-coding-based TAU using the Lempel'Ziv strategy asymptotically minimises both the update and paging costs with higher storage and computational overheads than the Bayesian-based one. There is some trade-off between the update/paging costs and storage/computational overheads in the two proposed schemes. The simulation results demonstrate that both proposed schemes outperform the existing comparable schemes for LTE systems in all of the performance metrics.

Published in:

IET Communications  (Volume:6 ,  Issue: 2 )