Improved particle filtering-based estimation of the number of competing stations in IEEE 802.11 networks

Jang Sub Kim, Erchin Serpedin, Dong Ryeol Shin

Research output: Contribution to journalArticle

26 Citations (Scopus)

Abstract

This letter proposes a new method to estimate the number of competing stations in IEEE 802.11 networks. Due to the nonlinear/non-Gaussian nature of measurement model, a nonlinear filtering algorithm, called the Gaussian mixture sigma point particle filter (GMSPPF), is proposed herein to estimate the number of competing stations. Since GMSPPF represents a better alternative to the conventional extended Kalman filter (EKF), unscented Kalman filter (UKF), particle filter (PF), and unscented particle filter (UPF) for nonlinear/non-Gaussian (or Gaussian) tracking problems, we apply this filter for IEEE 802.11 WLANs. GMSPPF provides a more viable means for tracking in any conditions the number of competing stations in IEEE 802.11 WLANs relative to EKF, UKF, PF, and UPF. Further, GMSPPF presents both high accuracy as well as prompt reactivity to changes in the network occupancy status. For the more accurate method (GMSPPF), the combined access mode is shown to maximize the system throughput by switching between the basic access mode and the RTS/CTS access mode.

Original languageEnglish
Pages (from-to)87-90
Number of pages4
JournalIEEE Signal Processing Letters
Volume15
DOIs
Publication statusPublished - 1 Dec 2008

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Keywords

  • Estimation
  • Filtering
  • Network

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering
  • Applied Mathematics

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