Energy harvesting personal cells - Traffic offloading and network throughput

Pei Shan Yu, Jemin Lee, Tony Q.S. Quek, Y. W.Peter Hong

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

Abstract

In this paper, we develop an analytical framework to evaluate the network throughput and traffic offloading efficiency in heterogeneous cellular networks (HCNs) with multiple energy-harvesting personal cells. The network consists of a tier of power-grid connected base-stations (BSs) and multiple tiers of energy-harvesting (personal) small cell access points (EH-SAPs). Each EH-SAP is personally owned by a priority user and becomes active only when its priority user requests communication and when its residual battery energy is sufficient to support the transmission. The energy arrival at each EH-SAP is modeled as a Bernoulli random process and the battery energy dynamics are modeled as a discrete time Markov chain. The network throughput is derived and its dependence on the energy arrival probability, cell association bias, and transmission power are examined based on the analysis. We show that, when the transmission power of EH-SAPs is sufficiently small, network throughput can be increased by increasing the density of EH-SAPs and by offloading more traffic to them. Our results offer insights on the design of spectral-efficient HCNs with EH-SAPs.

Original languageEnglish
Title of host publication2015 IEEE International Conference on Communications, ICC 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2184-2189
Number of pages6
ISBN (Electronic)9781467364324
DOIs
Publication statusPublished - 2015 Sep 9
EventIEEE International Conference on Communications, ICC 2015 - London, United Kingdom
Duration: 2015 Jun 82015 Jun 12

Publication series

NameIEEE International Conference on Communications
Volume2015-September
ISSN (Print)1550-3607

Other

OtherIEEE International Conference on Communications, ICC 2015
CountryUnited Kingdom
CityLondon
Period15-06-0815-06-12

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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