Adaptive gradient-based methods for adaptive power allocation in OFDM-based cognitive radio networks

Wei Chen Pao, Yung Fang Chen

Research output: Contribution to journalArticlepeer-review

26 Scopus citations

Abstract

A gradient-based method is designed for power allocation in orthogonal-frequency-division-multiplexing (OFDM)-based cognitive radio networks. The resource allocation problem subject to a mutual interference constraint is considered. We utilize the gradient descent approach to allocate power to subcarriers in cognitive radio (CR) networks. The proposed gradient-based power allocation method with a well-designed step size can approximate the optimal solution within a few iterations. Due to the derived equation for power allocation in an adaptive manner, the proposed method is feasible for adaptive power allocation in time-varying channels. The analysis for the selection of the step size is presented in this paper. For comparison purposes, a greedy power-loading method requiring numerous iterations is also designed for this power allocation problem. The proposed gradient-based method and the greedy power-loading method both have a computational complexity of O(N), but the proposed gradient-based method requires far fewer iterations. As demonstrated in the simulation results, the proposed gradient-based method with the adaptive step size has a fast rate to achieve a near-optimal solution within an extremely small number of iterations and has quite a low computational complexity of O(N).

Original languageEnglish
Article number6557515
Pages (from-to)836-848
Number of pages13
JournalIEEE Transactions on Vehicular Technology
Volume63
Issue number2
DOIs
StatePublished - Feb 2014

Keywords

  • Cognitive radio (CR)
  • gradient descent
  • orthogonal frequency-division multiplexing (OFDM)
  • power allocation

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