TY - JOUR
T1 - A factor-graph-based TOA location estimator
AU - Jhi, Hwa Lu
AU - Chen, Jung Chieh
AU - Lin, Chih Hung
AU - Huang, Chin Tseng
N1 - Funding Information:
Manuscript received March 24, 2011; revised January 11, 2012; accepted March 6, 2012. The associate editor coordinating the review of this paper and approving it for publication was M. Win. H. L. Jhi (corresponding author: [email protected]) and C. T. Huang are with the Department and Institute of Electrical Engineering, Minghsin University of Science and Technology, Hsinchu, Taiwan. J. C. Chen is with the Department of Optoelectronics and Communication Engineering, National Kaohsiung Normal University, Kaohsiung, Taiwan (e-mail: [email protected]). C. H. Lin is with the Department of Computer and Communication Engineering, Kun Shan University, Tainan, Taiwan. This work was supported by the National Science Council of the Republic of China under Grants NSC 99-2221-E-159 -008. Digital Object Identifier 10.1109/TWC.2012.040412.110520
PY - 2012/5
Y1 - 2012/5
N2 - A high-accuracy and low-complexity TOA-based algorithm is proposed to estimate mobile station (MS) location. First, a factor-graph-based distributive approach is used, which can work in a multi-state system as well. By effectively exchanging the available soft-information or stochastic property of the variables, this distributive approach can perform almost as well as conventional algorithm while requiring much less computational workload. Second, data screening method was applied to reduce complexity and data discrimination to improve accuracy. Simulation results demonstrate that this approach can maintain good accuracy while achieving low complexity. Since this approach is accurate and easy to implement, it will better satisfy the demands of real applications.
AB - A high-accuracy and low-complexity TOA-based algorithm is proposed to estimate mobile station (MS) location. First, a factor-graph-based distributive approach is used, which can work in a multi-state system as well. By effectively exchanging the available soft-information or stochastic property of the variables, this distributive approach can perform almost as well as conventional algorithm while requiring much less computational workload. Second, data screening method was applied to reduce complexity and data discrimination to improve accuracy. Simulation results demonstrate that this approach can maintain good accuracy while achieving low complexity. Since this approach is accurate and easy to implement, it will better satisfy the demands of real applications.
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U2 - 10.1109/TWC.2012.040412.110520
DO - 10.1109/TWC.2012.040412.110520
M3 - Article
AN - SCOPUS:84861460378
SN - 1536-1276
VL - 11
SP - 1764
EP - 1773
JO - IEEE Transactions on Wireless Communications
JF - IEEE Transactions on Wireless Communications
IS - 5
M1 - 6184261
ER -