Mobile Station Location Research Articles

Minimum Norm Multidimensional Scaling Solution for Mobile Station Localization in Wireless Sensors Network

Mobile station (MS) localization which plays an important role in the process of target continuous localization has received considerable attention. In this paper, a novel multidimensional scaling (MDS) method based on Minimum norm solution is proposed for passive emitter location in wireless networks. It is shown that the proposed approach is a generalization of the mobile localization method based on multidimensional scaling (MDS) analysis. Through computer simulations, we can see that the proposed algorithm has a better performance compared with classic MDS and subspace algorithms in time of arrival (TOA) measurements.

Simulation of ionospheric error on GPS signals due to changes in the direction of mobile station positions in differential GPS

Ionospheric propagation delay is one of the major sources of error in global positioning system (GPS) precision. Therefore, accurate estimation of the ionospheric delay is required to correct GPS positional calculations. This study investigates the simulation of ionospheric propagation delays of GPS signals caused by changes in the direction of mobile station positions in differential GPS. A comparison was made between short-distance (≤10 km) differential GPS ionospheric errors at rover stations and those at a single base station located at the University Kebangsaan Malaysia (2˚ 55' N, 101˚46'E). In this simulation, four different baseline orientations were considered: North (0˚), East (90˚), South (180˚) and West (270˚) of the University Kebangsaan Malaysia GPS station. Without consideration of any irregularities, the ionospheric errors at the northern rover station were nearly symmetrical to those at the southern station, which is elevation dependent. Similarly, there were nearly symmetrical ionospheric errors for the following orientation pairs: East (90˚) and West (270˚); Northwest (315˚) and Southeast (135˚); and Northeast (45˚) and Southwest (225˚). To maximize the quality of GPS positioning, all ionospheric errors need be considered so that accurate corrections can be made and precision can be enhanced.

MS Location Estimation with Genetic Algorithm

Intelligent transportation system (ITS) makes use of vehicle position to decrease the heavy traffic and improve service reliability of public transportation system. Many existing systems, such as global positioning system (GPS) and cellular communication systems, can be used to estimate vehicle location. The objective of wireless location is to determine the mobile station (MS) location in a wireless cellular communications system. The non-line-of-sight (NLOS) problem is the most crucial factor that it causes large measured error. In this paper, we present a novel positioning algorithm based on genetic algorithm (GA) to locate MS when three BSs are available for location purpose. Recently, GA are widely used as many various optimization problems. The proposed algorithm utilizes the intersections of three time of arrival (TOA) circles based on GA to estimate the MS location. The simulation results show that the proposed algorithms can really improve the location accuracy, even under severe NLOS conditions.

Mobile station positioning using time difference of arrival and received signal strength

In this paper, a new Mobile Station Positioning (MSP) technique is proposed and its performance is evaluated. The proposed technique combines the Received Signal Strength (RSS) and the Time Difference of Arrival (TDOA) techniques. Each RSS measurement yields a circle on which the Mobile Station (MS) may lie. Meanwhile, each TDOA measurement defines a hyperbola on which the MS may reside. The proposed hybrid TDOA/RSS technique uses Taylor series expansion to solve the hyperbolas and circles specified by the distance measurements obtained by the Base Stations (BSs). The MS position is determined based on Linear Least Squares (LLS) method in an iterative fashion. Without hardware modification, the proposed technique reduces location errors compared with either technique separately. Simulation results demonstrate superior performance over both TDOA and RSS techniques.

Hybrid Uplink-Time Difference of Arrival and Assisted-GPS Positioning Technique

A hybrid positioning system is merely one in which multiple systems are used for positioning purposes. This virtually always, though not necessarily, includes Global Positioning System (GPS) as it is the only global positioning network currently. Combination of mobile network and GPS positioning techniques provide a higher accuracy of mobile location than positions based on a standalone GPS or mobile network based positions. High accuracy of mobile position is mainly essential for emergency, military and many other location based services such as productivity enhancement, entertainment, position-based advertising, navigation, asset management and geographic information access. Assisted GPS, also known as A-GPS or AGPS, enhances the performance of the standard GPS in devices connected to the cellular network. This paper introduces a new hybrid technique for mobile location determination utilizing Universal Mobile Telecommunication System (UMTS) network, Mobile Station (MS) and GPS positioning characteristics. Different positioning techniques are chosen according to positioning parameters. The minimum required number of UMTS base stations, location measurement units and GPS satellites are calculated in this paper. The required number of GPS satellites is reduced from four satellites to three ones while using three dimension positioning and from three satellites to two ones at two dimension positioning. Moreover, MS receiver main functions including both network and GPS received paths to achieve output assisted data are discussed. In this paper many drawbacks such as indoor positioning, receiver high power consumption, delay in first time to fix position, low position accuracy as well as large number of required satellites and base stations are improved.

Calculation Of Mobile Location Based On TOA/SS Measurements

Localization of mobile station (MS) has now gained considerable attention. Since the hybrid measurements can help to improve the positioning accuracy, several hybrid localization methods have been proposed in the literature. However, the high performance estimator with the closed-form solution and complete performance analysis for time-of-arrival/signal strength (TOA/SS) localization technique is still an opening issue. Two TOA/SS localization algorithms with the closed-form solutions are proposed for the cases with or without uncertainty in the positions of base stations. Furthermore, performance analysis for the TOA/SS localization technique is presented. Both the theoretical variances and Cramer-Rao lower bounds (CRLBs) are derived and the relationship between the cases with or without uncertainty is given. The paper also proves that the TOA/SS scheme has a lower CRLB than the TOA (or SS) scheme. Theoretical analysis and simulations show that the proposed method can reach its CRLB.

Shannon Capacity Bound on Mobile Station Localization Accuracy in Urban Environments

The Federal Communications Commission (FCC) Phase II enhanced 911 (E-911) requirements have motivated increased interest in the challenge of localizing mobile sources in urban environments. The FCC E-911 Phase-II requires wireless carriers to provide the location of a 911 caller with accuracy of 100 meters in 67% of cases and 300 meters in 95% of cases. This work proposes an information theoretic bound on mobile station (MS) localization performance in urban environments that provides an alternative criterion for the MS localization performance evaluation. The proposed lower bound provides necessary, but not sufficient conditions for achieving arbitrary small probability of the localization error. The MS localization problem is modeled in the framework of communication via channels where the source location is modeled as a transmitted message which is encoded by the propagation conditions. The bound is evaluated for variety of propagation conditions predicted by a recently proposed statistical model of urban propagation conditions. The bound is demonstrated to apply to urban scenes of interest, and the sensitivity of the bound to changes in propagation conditions is discussed.

Indoor positioning based on statistical multipath channel modeling

In order to estimate the location of an indoor mobile station (MS), estimated time-of-arrival (TOA) can be obtained at each of several access points (APs). These TOA estimates can then be used to solve for the location of the MS. Alternatively, it is possible to estimate the location of the MS directly by incorporating the received signals at all APs in a direct estimator of position. This article presents a deeper analysis of a previously proposed maximum likelihood (ML)-TOA estimator, including a uniqueness property and the behavior in nonline-of-sight (NLOS) situations. Then, a ML direct location estimation technique utilizing all received signals at the various APs is proposed based on the ML-TOA estimator. The Cramer-Rao lower bound (CRLB) is used as a performance reference for the ML direct location estimator.

Non-line-of-sight Error Mitigation in Wireless Communication Systems

The need for determining the position of a mobile station (MS) is increasing rapidly in wireless communications systems. When there is non-line-of-sight (NLOS) path between the MS and base stations (BSs), it is possible to integrate many kinds of measurements to achieve more accurate measurements of the MS location. This paper proposed hybrid methods that utilize time of arrival (TOA) at five BSs and angle of arrival (AOA) information at the serving BS to determine the MS location in NLOS environments. The methods mitigate the NLOS effect simply by the weighted sum of the intersections between five TOA circles and the AOA line without requiring priori knowledge of NLOS error statistics. Simulation results show that the proposed methods always give superior performance than Taylor series algorithm (TSA) and the hybrid lines of position algorithm (HLOP).

Dilution of Position Calculation for MS Location Improvement in Wireless Communication Systems

Geometric dilution of precision (GDOP) represents the geometric effect of base stations (BSs) and mobile station (MS) on the relationship between measurement error and positioning determination error. When the measurement variances are equal to each other, GDOP could be the most appropriate selection criterion of location measurement units. GDOP expression has simpler form if all the measurements are with the same variance. For time of arrival (TOA) schemes, the maximum volume method of GDOP calculation doesn’t guarantee the optimal selection of the four measurement units. The conventional method for calculating GDOP is to use matrix inversion to all subsets. GDOP was originally used as a criterion for selecting the right 3D geometric configuration of satellites in global positioning systems (GPS). In this paper, we employ GDOP using the matrix inversion method to select appropriate BSs in cellular communication systems. The proposed BS selection criterion performs better than using the random subsets of four or five BSs chosen from all seven BSs. After BS selection, the proposed distance-weighted method and threshold method for TOA schemes can yield superior MS location estimation accuracy. For time difference of arrival (TDOA) schemes, the proposed BS selection criterion provides better MS location estimation. From simulation results, the performances of MS location strongly depend on the relative position of the MS and BSs. Therefore, it is very important to select a subset with the most appropriate BSs rapidly and reasonably for positioning.

A passive location system for single frequency networks using digital terrestrial TV signals

In this work, a passive location system for single frequency networks using digital terrestrial signals is proposed. A cross-correlation method that requires a correlation with fixed frequency was introduced for time delay estimation. The idea is first online reconstruction and update of the transmitted copy of the nearest base station (BS), and then uses this signal copy for correlation with the received signal samples. A time delay extraction method combined with K-mean clustering algorithm is developed. The minimum value of each cluster is extracted as the time delay of each BS. The BS identification can be modelled as a data association problem. A new gate that requires little statistical knowledge was utilised to solve time-of-arrival measurement uncertainty. Meanwhile, the data association strategy is also developed for successive data stream. Mobile station location is formulated as an optimisation problem and solved by a search processing. Simulations study was conducted to evaluate the system performance for different scenarios. The results demonstrate its robustness and high performance. Copyright © 2011 John Wiley & Sons, Ltd.

Adaptive Line Enhancement for Improved Uplink Time Difference of Arrival Localization

The problem of locating mobile stations (MS) in cellular systems based on uplink time difference of arrival (UTDOA) of MS signal at spatially separated base stations with known locations is addressed in this paper. Multipath fading and channel noise are the main factors resulting in inaccurate mobile station position estimation. Therefore, use of the normalized least mean square (NLMS) algorithm based adaptive line enhancer (ALE) followed by a correlator is proposed to obtain more precise time difference of arrival (TDOA) estimation. The proposed technique applies the ALE as a pre-filter to signal cross correlation, leading to improved accuracy in TDOA estimation and consequently more precise positioning of MS. The robustness of the proposed technique is examined and analyzed through computer simulations. Simulation results indicate superior performance of the proposed ALE-UTDOA estimator over the conventional cross correlation method.

Non-Line-of-Sight Error Mitigation in Wireless Communication Systems

When there is non-line-of-sight (NLOS) path between the mobile station (MS) and base stations (BSs), it is possible to integrate many kinds of measurements to achieve more accurate measurements of the MS location. This paper proposed hybrid methods that utilize time of arrival (TOA) at five BSs and angle of arrival (AOA) information at the serving BS to determine the MS location in NLOS environments. The methods mitigate the NLOS effect simply by the weighted sum of the intersections between five TOA circles and the AOA line without requiring priori knowledge of NLOS error statistics. Simulation results show that the proposed methods always give superior performance than Taylor series algorithm (TSA) and the hybrid lines of position algorithm (HLOP).

A study on the accuracy of AGA positioning algorithm in multipath environment

The quality of location-based services (LBS) services depends on the available accuracy of the used positioning method. There are generally several ones for wireless networks. The more accurate methods are way more expensive to implement. On the contrary, there are methods with lower accuracy and much lower costs as well. Received signal strength (RSS) method, which is described below, belongs to the latter case. The purpose of this paper is to describe a performance of adaptive geometric algorithm (AGA)for estimation of mobile station position in multipath environment. The algorithm is an improved version of basic geometric algorithm and it is compared to it as well as to Standard Least Squares method. The properties of the proposed algorithm are evaluated in a simulation and experimental scenario. Both scenarios are implemented in typical multipath conditions, which are crucial in wireless communication. Key words: Adaptive geometric algorithm, mobile positioning, received signal strength method, wireless networks.

On Data Fusion for Parametric-Model-Based Wireless Localization

In this paper, we present a data fusion framework for parametric-model-based wireless localization where the mobile station location is treated as a deterministic unknown vector. Three types of fusion schemes are presented: measurement fusion, estimate fusion and mixed fusion. Theoretical performance comparison among these schemes in terms of the estimation root mean square error via the weighted least square estimator (WLSE) is conducted. Such a performance metric coincides with the Cramer-Rao lower bound (CRLB) in the case of Gaussian noise. We show that, if the raw measurement vectors are correlated, then measurement fusion achieves the best performance, mixed fusion follows and estimate fusion is the worst. If the raw measurement vectors are uncorrelated, then these different fusion schemes achieve the same performance. Benefits that can be earned from data fusion for wireless localization are also investigated and numerical examples are presented to validate our theoretical analysis.

Applying Rprop Neural Network for the Prediction of the Mobile Station Location

Wireless location is the function used to determine the mobile station (MS) location in a wireless cellular communications system. When it is very hard for the surrounding base stations (BSs) to detect a MS or the measurements contain large errors in non-line-of-sight (NLOS) environments, then one need to integrate all available heterogeneous measurements to increase the location accuracy. In this paper we propose a novel algorithm that combines both time of arrival (TOA) and angle of arrival (AOA) measurements to estimate the MS in NLOS environments. The proposed algorithm utilizes the intersections of two circles and two lines, based on the most resilient back-propagation (Rprop) neural network learning technique, to give location estimation of the MS. The traditional Taylor series algorithm (TSA) and the hybrid lines of position algorithm (HLOP) have convergence problems, and even if the measurements are fairly accurate, the performance of these algorithms depends highly on the relative position of the MS and BSs. Different NLOS models were used to evaluate the proposed methods. Numerical results demonstrate that the proposed algorithms can not only preserve the convergence solution, but obtain precise location estimations, even in severe NLOS conditions, particularly when the geometric relationship of the BSs relative to the MS is poor.

Improved Taylor-Series Expansion for MS Location Estimation

The objective of wireless location is to determine the mobile station (MS) location in a wireless cellular communications system. Due to the measurement with large errors, location schemes give poorer performance in non-line-of-sight (NLOS) environments. To determine MS location, Taylor-series algorithm (TSA) is commonly used scheme. TSA can give a least-square (LS) solution to a set of simultaneous linearized equations. The disadvantage of TSA is the need for an initial position guess to start the solution process. The iteration process may not converge due to a poor initial estimate of the MS location. To improve the location accuracy with less complexity, the initial MS location selection criterion is proposed. Numerical results demonstrate that the proposed criterion always provides more accurate positioning.

Robust Mobile Location Estimation Using Hybrid TOA/AOA Measurements in Cellular Systems

Estimating a location of mobile station is considerable interest in wireless cellular systems. This letter deals with a hybrid time-of-arrival (TOA)/angle-of-arrival (AOA) mobile location estimation under relatively low signal-to-noise ratio and moderately nonline-of-sight (NLOS) scenarios. To reduce location estimation errors, a robust estimator for hybrid TOA/AOA location systems is proposed by using the minimax mean-squared error (MSE) criterion. Simulation results demonstrate that the proposed estimator significantly outperforms the other least squares estimators.

Mobile Location Estimation in Wireless Communication Systems

The objective of wireless location is to determine the mobile station (MS) location in a wireless cellular communications system. When signals are propagated through non-line-of-sight (NLOS) paths, the measurements at the base stations (BSs) contain large errors which result in poor detectability of an MS by the surrounding BSs. In those situations, it is necessary to integrate all available heterogeneous measurements to improve location accuracy. This paper presents hybrid methods that combine time of arrival (TOA) at three BSs and angle of arrival (AOA) information at the serving BS to obtain a location estimate for the MS. The proposed methods mitigate the NLOS effect by using the weighted sum of the intersections between three TOA circles and the AOA line without requiring the a priori knowledge of NLOS error statistics. Numerical results show that all positioning methods offer improved estimation accuracy over those which rely on the two circles and two lines. The proposed methods always achieve better location accuracy than the Taylor series algorithm (TSA) and the hybrid lines of position algorithm (HLOP) do, regardless of the NLOS error statistics.

A Mobile-aware Adaptive Rate Control Scheme for Improving the User Perceived QoS of Multimedia Streaming Services in Wireless Broadband Networks

Recently, due to the prevalence of various mobile devices and wireless broadband networks, there has been a significant increase in interest and demand for multimedia streaming services such as the mobile IPTV. In such a wireless broadband network, transmitting a continuous stream of multimedia data is difficult to achieve due to mobile stations (MSs) movement. Providing Quality of Service (QoS) for multimedia video streaming applications requires the server and/or client to be network-aware and adaptive. Therefore, in order to deploy a mobile IPTV service in wireless broadband networks, offering users efficient wireless resource utilization and seamlessly offering user perceived QoS are important issues. In this paper, we propose a new adaptive streaming scheme, called MARC (Mobile-aware Adaptive Rate Control), which adjusts the quality of bit-stream and transmission rate of video streaming based on the wireless channel status and network status. The proposed scheme can control the rate of multimedia streaming to be suitable for the wireless channel status by using awareness information of the wireless channel quality and the mobile station location. The proposed scheme can provide a seamless multimedia playback service in wireless broadband networks in addition to improving the QoS of multimedia streaming services. The proposed MARC scheme alleviates the discontinuity of multimedia playback and allocates a suitable client buffer to the wireless broadband network. The simulation results demonstrate the effectiveness of our proposed scheme.