• DocumentCode
    2712922
  • Title

    Dynamic-KNN: A novel locating method in WLAN based on Angle of Arrival

  • Author

    Roshanaei, Mahnaz ; Maleki, Mina

  • Author_Institution
    Iran Telecommun. Res. Center, Commun. Technol. Inst., Tehran, Iran
  • Volume
    2
  • fYear
    2009
  • fDate
    4-6 Oct. 2009
  • Firstpage
    722
  • Lastpage
    726
  • Abstract
    Location estimation as one of the most popular research areas has been recently attended because of wide range of its applications. K Nearest Neighbor (KNN) is a basic deterministic algorithm for locating which is widely used in fingerprinting approach. The performance of the KNN can be improved extensively by employing appropriate selection algorithm. In this paper, a novel algorithm called Dynamic KNN (D-KNN) which uses Angle of Arrival (AOA) and KNN as a hybrid method is proposed. This method comparing with KNN algorithm with constant K, selects the best number of nearest neighbors dynamically. It utilizes the adaptive antenna system to determine the user locative area by intersection of several obtained AOA. The best K neighbors which are located in the determined area can be selected to employ in the KNN. Analysis and simulation results are reported the best overall performance of D-KNN in different conditions.
  • Keywords
    direction-of-arrival estimation; mobile computing; wireless LAN; K nearest neighbor; WLAN; angle of arrival; dynamic-KNN; location estimation; Adaptive arrays; Adaptive systems; Communications technology; Fingerprint recognition; Hardware; Heuristic algorithms; Industrial electronics; Nearest neighbor searches; Time measurement; Wireless LAN; Angle of Arrival; Indoor Positioning; K Nearest Neighbor (KNN); Location Fingerprinting;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics & Applications, 2009. ISIEA 2009. IEEE Symposium on
  • Conference_Location
    Kuala Lumpur
  • Print_ISBN
    978-1-4244-4681-0
  • Electronic_ISBN
    978-1-4244-4683-4
  • Type

    conf

  • DOI
    10.1109/ISIEA.2009.5356349
  • Filename
    5356349