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Wireless Personal Communications

, Volume 108, Issue 4, pp 2461–2476 | Cite as

PSO Optimized Hidden Markov Model Performance Analysis for IEEE 802.16/WiMAX Standard

  • Shaghayegh KordnooriEmail author
  • Hamidreza Mostafaei
  • Mohammad Hassan Behzadi
Article
  • 19 Downloads

Abstract

The discrete channel hidden Markov models indicate the temporal statistical characteristics of the generated error sequences by fading channels with memory precisely. In this paper first the optimal order of the hidden Markov models is estimated using Baum Welch algorithm (BWA) with comparing statistics such as average loglikelihood and autocorrelation function for error modelling of IEEE 802.16/WiMAX standard. As a perfect alternative to HMM error models, a new efficient stochastic swarm intelligent-based particle swarm optimization (PSO)-HMM is suggested for this standard to find the global and optimal solution. Comparing the proposed method with the conventional (BWA) by performing numerical simulations using error sequences of various lengths, the results indicate the superiority of the PSO approach even when the target sequences are as short as 2000 in length; moreover, the appropriateness of the PSO-HMM is investigated for different sampling periods. It can be concluded that the PSO with two states arrives at high level of accuracy in contrast to HMM with much higher number of states. For validating the proposed method, the burst error statistics of the PSO-HMM with respect to the autocorrelation function and error free interval distribution of the original error sequence are presented. The simulation results indicate that the PSO-HMM has better performance to find the optimal model parameters more stable than (BWA).

Keywords

Particle swarm optimization (PSO) Hidden Markov model Baum Welch algorithm IEEE 802.16 

Notes

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Statistics, Science and Research BranchIslamic Azad UniversityTehranIran
  2. 2.Department of Statistics, North Tehran BranchIslamic Azad UniversityTehranIran

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