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LeZi-Update: An Information-Theoretic Framework for Personal Mobility Tracking in PCS Networks

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Abstract

The complexity of the mobility tracking problem in a cellular environment has been characterized under an information-theoretic framework. Shannon's entropy measure is identified as a basis for comparing user mobility models. By building and maintaining a dictionary of individual user's path updates (as opposed to the widely used location updates), the proposed adaptive on-line algorithm can learn subscribers' profiles. This technique evolves out of the concepts of lossless compression. The compressibility of the variable-to-fixed length encoding of the acclaimed Lempel–Ziv family of algorithms reduces the update cost, whereas their built-in predictive power can be effectively used to reduce paging cost.

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Authors and Affiliations

  1. Center for Research in Wireless Mobility and Networking (CReWMaN), Department of Computer Science and Engineering, The University of Texas at Arlington, Arlington, TX, 76019-0015, USA

    Amiya Bhattacharya & Sajal K. Das

Authors
  1. Amiya Bhattacharya
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  2. Sajal K. Das
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Bhattacharya, A., Das, S.K. LeZi-Update: An Information-Theoretic Framework for Personal Mobility Tracking in PCS Networks. Wireless Networks 8, 121–135 (2002). https://doi.org/10.1023/A:1013759724438

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