User request prediction increases energy efficiency in AWGN channels: (((Invited paper)

Wei Huang, Wei Chen, H. Vincent Poor

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

1 Scopus citations

Abstract

Proactively pushing content to users has emerged as a promising way of coping with the explosively growing traffic demand of next-generation mobile networks. However, it is still unclear whether content pushing can improve the energy efficiency of hard delay-constrained communications over additive white Gaussian noise (AWGN) channels. With pushing, the energy consumption can be reduced by increasing the available transmission time. But if the user never needs the pushed content, pushing may result in wasted energy. Based on the random content request delay, this paper derives the content request probability threshold that determines whether a content file should be pushed under the hard delay constraint. Moreover, an optimal strategy to allocate transmission power in content pushing and on-demand delivery phases is also proposed. It is shown that the energy efficiency of systems with pushing can be significantly improved as the content request probability increases. Numerical results validate the effectiveness of the proposed power allocation strategy, compared with the on-demand scheme.

Original languageEnglish (US)
Title of host publication18th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-5
Number of pages5
ISBN (Electronic)9781509030088
DOIs
StatePublished - Dec 19 2017
Event18th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2017 - Sapporo, Japan
Duration: Jul 3 2017Jul 6 2017

Publication series

NameIEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC
Volume2017-July

Other

Other18th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2017
CountryJapan
CitySapporo
Period7/3/177/6/17

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering
  • Computer Science Applications
  • Information Systems

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    Huang, W., Chen, W., & Poor, H. V. (2017). User request prediction increases energy efficiency in AWGN channels: (((Invited paper). In 18th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2017 (pp. 1-5). [8227677] (IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC; Vol. 2017-July). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SPAWC.2017.8227677