QoS-driven power control for fading channels with arbitrary input distributions

Gozde Ozcan, M. Cenk Gursoy

Research output: Chapter in Book/Entry/PoemConference contribution

6 Scopus citations

Abstract

In this paper, the optimal power control policy that maximizes the effective capacity for arbitrary input distributions in fading channels subject to an average power constraint is studied. A low-complexity power control algorithm is proposed. In addition, energy efficiency is investigated by characterizing both the minimum energy per bit and wideband slope for arbitrary signaling in the low-power regime when channel side information (CSI) is available only at the receiver. With perfect CSI at both the transmitter and receiver, the optimal power adaptation strategy in this regime is also determined. Through numerical results, performance comparison with constant power scheme and optimal power adaptation strategy for different signal constellations and Gaussian signals is given. The impact of QoS constraints, input distributions, and average transmit power level on the proposed power control policy, maximum achievable effective capacity and energy efficiency is analyzed.

Original languageEnglish (US)
Title of host publication2014 IEEE International Symposium on Information Theory, ISIT 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1381-1385
Number of pages5
ISBN (Print)9781479951864
DOIs
StatePublished - 2014
Event2014 IEEE International Symposium on Information Theory, ISIT 2014 - Honolulu, HI, United States
Duration: Jun 29 2014Jul 4 2014

Publication series

NameIEEE International Symposium on Information Theory - Proceedings
ISSN (Print)2157-8095

Other

Other2014 IEEE International Symposium on Information Theory, ISIT 2014
Country/TerritoryUnited States
CityHonolulu, HI
Period6/29/147/4/14

Keywords

  • Effective capacity
  • MMSE
  • QoS constraints
  • energy efficiency
  • fading channel
  • low-power regime
  • mutual information
  • optimal power control

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Information Systems
  • Modeling and Simulation
  • Applied Mathematics

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