Stochastic geometry model for multi-channel fog radio access networks

Mostafa Emara, Hesham Elsawy, Sameh Sorour, Samir Al-Ghadhban, Mohamed Slim Alouini, Tareq Y. Al-Naffouri

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

Cache-enabled base station (BS) densification, denoted as a fog radio access network (F-RAN), is foreseen as a key component of 5G cellular networks. F-RAN enables storing popular files at the network edge (i.e., BS caches), which empowers local communication and alleviates traffic congestions at the core/backhaul network. The hitting probability, which is the probability of successfully transmitting popular files request from the network edge, is a fundamental key performance indicator (KPI) for F-RAN. This paper develops a scheduling aware mathematical framework, based on stochastic geometry, to characterize the hitting probability of F-RAN in a multi-channel environment. To this end, we assess and compare the performance of two caching distribution schemes, namely, uniform caching and Zipf caching. The numerical results show that the commonly used single channel environment leads to pessimistic assessment for the hitting probability of F-RAN. Furthermore, the numerical results manifest the superiority of the Zipf caching scheme and quantify the hitting probability gains in terms of the number of channels and cache size.

Original languageEnglish
Title of host publication2017 15th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, WiOpt 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9783901882906
DOIs
StatePublished - 27 Jun 2017

Publication series

Name2017 15th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, WiOpt 2017

Bibliographical note

Publisher Copyright:
© 2017 IFIP.

Keywords

  • Caching system
  • F-RAN
  • Multichannel
  • Stochastic geometry

ASJC Scopus subject areas

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

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