• DocumentCode
    3348006
  • Title

    Use of a Simplified Maximum Likelihood Function in a WLAN-Based Location Estimation

  • Author

    Hara, Shinsuke ; Anzai, Daisuke

  • Author_Institution
    Grad. Sch. of Eng., Osaka City Univ., Osaka
  • fYear
    2009
  • fDate
    5-8 April 2009
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    In a location estimation with the received signal strength indication (RSSI) of a wireless signal in an area, the maximum likelihood (ML) function should match the real statistical property of the RSSI in the area. For a wireless local area network (WLAN)-based RSSI location estimation with a wideband signal in an office environment, the wideband signal experiences frequency selectively Rayleigh fading, so a complicated ML function containing several channel parameters needs to be derived in the environment. This paper shows that a simplified ML function containing only two channel parameters, which is optimum for a narrowband signal, is also applicable to an IEEE 802.11 g WLAN-based location estimation with a wideband signal. Computer simulation and experimental results show that the use of the simplified ML function introduces almost no degradation in the location estimation performance in typical office environments, as compared with the use of an exact ML function.
  • Keywords
    fading; maximum likelihood estimation; wireless LAN; IEEE 802.11 g WLAN-based location estimation; RSSI location estimation; frequency selectively Rayleigh fading; narrowband signal; received signal strength indication; simplified maximum likelihood function; statistical property; wireless local area network; wireless signal; Communications Society; Computer simulation; Degradation; Frequency estimation; Maximum likelihood estimation; Media Access Protocol; Narrowband; Rayleigh channels; Wideband; Wireless LAN;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Wireless Communications and Networking Conference, 2009. WCNC 2009. IEEE
  • Conference_Location
    Budapest
  • ISSN
    1525-3511
  • Print_ISBN
    978-1-4244-2947-9
  • Electronic_ISBN
    1525-3511
  • Type

    conf

  • DOI
    10.1109/WCNC.2009.4918013
  • Filename
    4918013