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Evaluation of Dynamic Channel and Power Assignment for Cognitive Networks

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An Erratum to this article was published on 30 May 2012

Abstract

In this paper, we develop a unifying optimization formulation to describe the Dynamic Channel and Power Assignment (DCPA) problem and an evaluation method for comparing DCPA algorithms. DCPA refers to the allocation of transmit power and frequency channels to links in a cognitive network so as to maximize the total number of feasible links while minimizing the aggregate transmit power. We apply our evaluation method to five representative DPCA algorithms proposed in the literature. This comparison illustrates the tradeoffs between control modes (centralized versus distributed) and channel/power assignment techniques. We estimate the complexity of each algorithm. Through simulations, we evaluate the effectiveness of the algorithms in achieving feasible link allocations in the network, and their power efficiency. Our results indicate that, when few channels are available, the effectiveness of all algorithms is comparable and thus the one with smallest complexity should be selected. The Least Interfering Channel and Iterative Power Assignment algorithm does not require cross-link gain information, has the overall lowest run time, and achieves the highest feasibility ratio of all the distributed algorithms; however, this comes at a cost of higher average power per link.

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Authors and Affiliations

  1. Virginia Polytechnic Institute & State University, Blacksburg, VA, USA

    Juan D. Deaton, Syed A. Ahmad, Umesh Shukla, Ryan E. Irwin, Luiz A. DaSilva & Allen B. MacKenzie

  2. Idaho National Laboratory, Idaho Falls, ID, USA

    Juan D. Deaton

  3. CTVR, Trinity College Dublin, Dublin, Ireland

    Luiz A. DaSilva

Authors
  1. Juan D. Deaton
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  2. Syed A. Ahmad
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  3. Umesh Shukla
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  4. Ryan E. Irwin
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  5. Luiz A. DaSilva
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  6. Allen B. MacKenzie
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Corresponding author

Correspondence to Juan D. Deaton.

Additional information

This work is partially supported by the Idaho National Laboratory (INL) Ph.D. Candidate Program and Virginia Tech Bradley Fellowship. Work supported by the INL is done under Battelle Energy Alliance, LLC under Contract No. DE-AC07-05ID14517 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a nonexclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Department of Energy or the U.S. Government.

An erratum to this article can be found at http://dx.doi.org/10.1007/s11277-012-0630-6

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Deaton, J.D., Ahmad, S.A., Shukla, U. et al. Evaluation of Dynamic Channel and Power Assignment for Cognitive Networks. Wireless Pers Commun 57, 5–18 (2011). https://doi.org/10.1007/s11277-010-0003-y

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  • DOI: https://doi.org/10.1007/s11277-010-0003-y

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