An improved cell type classification for random walk modeling in cellular networks

Yu-Chee Tseng*, Wei Neng Hung

*Corresponding author for this work

Research output: Contribution to journalArticle

13 Scopus citations

Abstract

In an earlier paper by Akyildiz et al., it is shown how to classify cell types in a cellular network based on the random walk model; the number of states is reduced from a naive classification of (3n 2+3n-5) to n(n+1)/2 in a hexagonal configuration, where n is the number of layers of cells. By using a reflection relation, this paper shows that the number of states can be further reduced to (n + 1)(n + 3)/4 if n is odd, and n(n + 4)/4 if n is even. These numbers are about half of that of Akyildiz et al. Simulation experiments indicate that our approach significantly reduces the computational costs in the related probability derivation.

Original languageEnglish
Pages (from-to)337-339
Number of pages3
JournalIEEE Communications Letters
Volume5
Issue number8
DOIs
StatePublished - 1 Aug 2001

Keywords

  • Cellular network
  • Location management
  • Personal communication services (PCS)
  • Random walk
  • Wireless communication

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