Adaptive Mobile Positioning in WCDMA Networks
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Adaptive Mobile Positioning in WCDMA Networks B. Dong Department of Electrical and Computer Engineering, Queen’s University, Kingston, ON, Canada K7L 3N6
Xiaodong Wang Department of Electrical Engineering, Columbia University, New York, NY 10027-4712, USA Email: [email protected] Received 6 November 2004; Revised 14 March 2005 We propose a new technique for mobile tracking in wideband code-division multiple-access (WCDMA) systems employing multiple receive antennas. To achieve a high estimation accuracy, the algorithm utilizes the time difference of arrival (TDOA) measurements in the forward link pilot channel, the angle of arrival (AOA) measurements in the reverse-link pilot channel, as well as the received signal strength. The mobility dynamic is modelled by a first-order autoregressive (AR) vector process with an additional discrete state variable as the motion offset, which evolves according to a discrete-time Markov chain. It is assumed that the parameters in this model are unknown and must be jointly estimated by the tracking algorithm. By viewing a nonlinear dynamic system such as a jump-Markov model, we develop an efficient auxiliary particle filtering algorithm to track both the discrete and continuous state variables of this system as well as the associated system parameters. Simulation results are provided to demonstrate the excellent performance of the proposed adaptive mobile positioning algorithm in WCDMA networks. Keywords and phrases: mobility tracking, Bayesian inference, jump-Markov model, auxiliary particle filter.
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INTRODUCTION
Mobile positioning [1, 2, 3, 4], that is, estimating the location of a mobile user in wireless networks, has recently received significant attention due to its various potential applications in location-based services, such as location-based billing, intelligent transportation systems [5], and the enhanced-911 (E-911) wireless emergence services [6]. In addition to facilitating these location-based services, the mobility information can also be used by a number of control and management functionalities in a cellular system, such as mobile location indication, handoff assistance [3], transmit power control, and admission control. Various mobile positioning schemes have been proposed in the literature. Typically, they are based on the measurements of received signal strength [7], time of arrival (TOA) or time difference of arrival (TDOA) [8], and angle of arrival (AOA) [4]. In [4], a hybrid TDOA/AOA method is proposed and the mobile user location is calculated using a two-step least-square estimator. Although this scheme offers a higher location accuracy than the pure TDOA scheme, there is still This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
a gap between its performance and the optimal performance since it is based on a linear approximation of the highly nonlinear mobility model. Moreover, that work deals
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