• DocumentCode
    118468
  • Title

    Performance improvement techniques for RSSI based localization methods

  • Author

    Al Shayokh, Md ; Alkasi, Ugur ; Partal, H.P.

  • Author_Institution
    Dept. of ECE, Yildiz Tech. Univ., Istanbul, Turkey
  • fYear
    2014
  • fDate
    13-15 Feb. 2014
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Performance improvement techniques for two popular RSSI based indoor localization methods have been studied experimentally by using Wi-Fi modems. The improvement of RF Fingerprinting and RSSI Multi-lateration methods have been suggested from different aspects for both line-of-sight (LoS) and non-line-of-sight (nLoS) medium in an indoor environment. Various testing scenarios have been examined for comparison of the two methods, as the performance level in RF Fingerprinting is mainly depend on the number of modems, as well as the density of training data and, the multilateration method is mainly depend on correctly modelling of the path loss exponent. Optimizing and defining a unique path loss exponent for each of the wireless transmitter modems, testing in a LoS and a nLoS medium, changing the number of transmitters, etc, have been tried and performance plots have been shown for comparison purposes.
  • Keywords
    indoor communication; modems; radio transmitters; wireless LAN; RF fingerprinting; RSSI indoor localization methods; RSSI multilateration; Wi-Fi modems; indoor environment; nLoS medium; nonline-of-sight medium; path loss exponent; performance improvement; wireless transmitter modems; Accuracy; Fingerprint recognition; IEEE 802.11 Standards; Indoor environments; Modems; Radio frequency; Radio transmitters; Indoor localization; LBS; RF fingerprinting; RSS(Receive Signal Strength); Signal strength to distance conversion; WiFi based localization; lateration technique;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical Information and Communication Technology (EICT), 2013 International Conference on
  • Conference_Location
    Khulna
  • Print_ISBN
    978-1-4799-2297-0
  • Type

    conf

  • DOI
    10.1109/EICT.2014.6777839
  • Filename
    6777839