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Computational Intelligence for Pattern Recognition pp 275–290Cite as

Particle Swarm Optimization Based HMM Parameter Estimation for Spectrum Sensing in Cognitive Radio System

Part of the Studies in Computational Intelligence book series (SCI,volume 777)

Abstract

Spectrum Estimation has emerged as the major bottleneck for the development of advanced technologies (IoT and 5G) that demand for a unperturbed continuous availability of the spectrum resources. Opportunistic dynamic access of spectrum by unlicensed users when the licensed user is not using the resources is seen as a solution to the pressing issue of spectrum scarcity. The idea proposed for spectrum estimation is to model the Cognitive Radio (CR) network as Hidden Markov Model (HMM). The spectral estimation is done once in a frame. 100 such frames with 3000 slots each is considered for performing the experiment, assuming that the PU activity is known for a fraction of \(3.33\%\) of the slots i.e., for 100 slots. The parameters of the HMM are estimated by maximizing the generating probability of the sequence using the Particle Swarm Optimization (PSO). For the typical values of the network parameters, the experiments are performed and the results are presented. A novel sum squared error minimization based “Empirical Match” algorithm is proposed for an improved latent sequence estimation.

Keywords

  • Computational intelligence
  • Particle swarm optimization
  • Empirical match algorithm
  • Cognitive radio
  • Spectrum estimation
  • Hidden Markov model

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  • DOI: 10.1007/978-3-319-89629-8_10
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Author information

Authors and Affiliations

  1. Department of Electronics and Communication Engineering, National Institute of Technology Trichy, Tiruchirapalli, 620015, Tamil Nadu, India

    Yogesh Vineetha, E. S. Gopi & Shaik Mahammad

Authors
  1. Yogesh Vineetha
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  2. E. S. Gopi
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  3. Shaik Mahammad
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Corresponding author

Correspondence to E. S. Gopi .

Editor information

Editors and Affiliations

  1. University of Alberta, Edmonton, Alberta, Canada

    Prof. Witold Pedrycz

  2. National Taiwan University of Science and Technology, Taipei, Taiwan

    Shyi-Ming Chen

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Vineetha, Y., Gopi, E.S., Mahammad, S. (2018). Particle Swarm Optimization Based HMM Parameter Estimation for Spectrum Sensing in Cognitive Radio System. In: Pedrycz, W., Chen, SM. (eds) Computational Intelligence for Pattern Recognition. Studies in Computational Intelligence, vol 777. Springer, Cham. https://doi.org/10.1007/978-3-319-89629-8_10

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  • DOI: https://doi.org/10.1007/978-3-319-89629-8_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-89628-1

  • Online ISBN: 978-3-319-89629-8

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