A sufficient condition for tail asymptotics of SIR distribution in downlink cellular networks

Naoto Miyoshi, Tomoyuki Shirai

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

We consider the spatial stochastic model of single-tier downlink cellular networks, where the wireless base stations are deployed according to a general stationary point process on the Euclidean plane with general i.i.d. propagation effects. Recently, Ganti & Haenggi (2016) consider the same general cellular network model and, as one of many significant results, derive the tail asymptotics of the signal-to-interference ratio (SIR) distribution. However, they do not mention any conditions under which the result holds. In this paper, we compensate their result for the lack of the condition and expose a sufficient condition for the asymptotic result to be valid. We further illustrate some examples satisfying such a sufficient condition and indicate the corresponding asymptotic results for the example models. We give also a simple counterexample violating the sufficient condition.

Original languageEnglish
Title of host publication2016 14th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, WiOpt 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509013111
DOIs
Publication statusPublished - Jun 15 2016
Event14th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, WiOpt 2016 - Tempe, United States
Duration: May 9 2016May 13 2016

Publication series

Name2016 14th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, WiOpt 2016

Other

Other14th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, WiOpt 2016
Country/TerritoryUnited States
CityTempe
Period5/9/165/13/16

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Control and Optimization
  • Modelling and Simulation

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