TY - GEN
T1 - Mobile localization based on improved Non-Line-of-Sight classification
AU - Muqaibel, Ali H.
AU - Al-Nimnim, Refat A.
AU - Landolsi, Mohamed A.
AU - Al-Ahmari, Abdullah S.
PY - 2010
Y1 - 2010
N2 - One of the main problems facing accurate localization using Time-of-Arrival (TOA) measurements in wireless communication systems is Non-Line-of-Sight (NLOS) propagation. Classification is among the important NLOS mitigation approaches whereby the system attempts to identify and localize with the LOS base stations (BSs) only. In this paper, the impact of the number of NLOS BSs and their geometrical distribution on the localization process is investigated. With the use of a residual test (RT) classification algorithm, it is shown that, under certain conditions, the system that localizes with all BSs (including both LOS and NLOS) can benefit from error cancellation, and may perform better than the system that implements "pure" classification. Based on this observation, it is concluded that BSs identified as NLOS should not always be dropped, and a modified classification algorithm is proposed. The new algorithm drops BSs identified as NLOS only when there are enough geometrically "well distributed" BSs to localize with. Simulation results show that the proposed algorithm can outperform other conventional classification schemes.
AB - One of the main problems facing accurate localization using Time-of-Arrival (TOA) measurements in wireless communication systems is Non-Line-of-Sight (NLOS) propagation. Classification is among the important NLOS mitigation approaches whereby the system attempts to identify and localize with the LOS base stations (BSs) only. In this paper, the impact of the number of NLOS BSs and their geometrical distribution on the localization process is investigated. With the use of a residual test (RT) classification algorithm, it is shown that, under certain conditions, the system that localizes with all BSs (including both LOS and NLOS) can benefit from error cancellation, and may perform better than the system that implements "pure" classification. Based on this observation, it is concluded that BSs identified as NLOS should not always be dropped, and a modified classification algorithm is proposed. The new algorithm drops BSs identified as NLOS only when there are enough geometrically "well distributed" BSs to localize with. Simulation results show that the proposed algorithm can outperform other conventional classification schemes.
KW - Localization
KW - Mobile positioning
KW - NLOS classification
KW - Non-Line-of-Sight (NLOS)
KW - Time-of-arrival (ToA)
UR - http://www.scopus.com/inward/record.url?scp=77954546632&partnerID=8YFLogxK
U2 - 10.1109/ICTEL.2010.5478773
DO - 10.1109/ICTEL.2010.5478773
M3 - Conference contribution
AN - SCOPUS:77954546632
SN - 9781424452477
T3 - ICT 2010: 2010 17th International Conference on Telecommunications
SP - 368
EP - 374
BT - ICT 2010
ER -