Analysis of cellular mobile radio

  • Avner Friedman
Chapter
Part of the The IMA Volumes in Mathematics and its Applications book series (IMA, volume 83)

Abstract

Recent growth in the demand for wireless services has increased interest in queueing-theoretic models for cellular mobile radio systems. such models differ fundamentally from traditional teletraffic models because in cellular systems spatial structure is important. On January 27, 1995 Paul E. Wright from AT&T Bell Laboratories discussed various queueing models for cellular systems and showed how techniques from statistical physics may be used to analyze and obtain insight into their performance; this work will appear in [1]. One of the most important results of that paper is that, in rather generic situations, even if resources are uniformly distributed and the demand for service is the same in each cell, the density of active users may vary, being persistently high in some cells and persistently low in others, resulting in overall uneven quality of service.

Keywords

Partition Function Code Division Multiple Access Blocking Probability Code Division Multiple Access System Reuse Factor 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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References

  1. [1]
    P.E. Wright, A.G. Greenberg, A. Millis, P. Mitra and J. TungMultiple behavior in interacting queues and related cellular systemsto appearGoogle Scholar
  2. [2]
    A. Friedman, Mathematicsin Industrial ProblemsPart 7, IMA Volume 67, Springer-Verlag, New York (1995).Google Scholar
  3. [3]
    V.H. McDonaldThe cellular conceptBell System Technical Journal, 58 (1979), 15–41.Google Scholar
  4. [4]
    D. ParsonThe Mobile Radio Propagation ChannelJohn Wiley & Sons, New York (1992) (Reprinted 1994).Google Scholar
  5. [5]
    F.P. KellyStochastic models of computer communication systemsJournal of the Royal Statistical Society B, 85 (1985), 379–395.Google Scholar
  6. [6]
    K. HuangStatistical Mechanics2nd ed., John Wiley & Sons, New York (1987).MATHGoogle Scholar
  7. [7]
    G. Parisi, StatisticalField TheoryAddison-Wesley, Redwood City, Calif. (1988).Google Scholar
  8. [8]
    W. Whitt, Heavy-trafficapproximation for service systems with blockingAT&T Laboratories Technical Journal, 63 (1989), 689–708.MathSciNetGoogle Scholar
  9. [9]
    F.P. KellyBlocking probabilities in large circuit switched networksAdvanced Applied Probability, 18 (1986), 473–505.MATHCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 1997

Authors and Affiliations

  • Avner Friedman
    • 1
  1. 1.Institute for Mathematics and its ApplicationsUniversity of MinnesotaMinneapolisUSA

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