Utility-based power control for peer-to-peer cognitive radio networks with heterogeneous QoS constraints

Nikolaos Gatsis, Antonio G. Marques, Georgios B Giannakis

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

23 Scopus citations

Abstract

Transmit-power control is a critical task in cognitive radio (CR) networks. In the present contribution, adherence to hierarchies between primary and secondary users in a peer-to-peer CR network is enabled through distributed power control. Hierarchies are effected by imposing minimum and maximum bounds on a quality-of-service (QoS) metric, such as communication rate. These bounds translate to signal-to-interference-plus-noise ratio (SINR) constraints. Furthermore, a utility function captures each user's satisfaction with the received SINR. The novel power control strategy maximizes the total utility while respecting individual SINR constraints - a task recast as a convex optimization problem under a suitable relaxation. Sufficient conditions, realistic for practical CR networks, are provided to obtain the optimal power allocation from the solution of the relaxed problem. Finally, a low-overhead distributed algorithm for optimal power control is developed, and tested against competing alternatives via simulations.

Original languageEnglish (US)
Title of host publication2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP
Pages2805-2808
Number of pages4
DOIs
StatePublished - Sep 16 2008
Event2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP - Las Vegas, NV, United States
Duration: Mar 31 2008Apr 4 2008

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Other

Other2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP
Country/TerritoryUnited States
CityLas Vegas, NV
Period3/31/084/4/08

Keywords

  • Cognitive radios
  • Distributed algorithms
  • Optimization methods
  • Power control
  • QoS constraints

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