Observed Time Difference Of Arrival Research Articles

Multi-frequency smartphone positioning performance evaluation: insights into A-GNSS PPP-B2b services and beyond

In August 2023, Xiaomi unveiled the Redmi K60 Ultra, the first multi-frequency smartphone integrated with BeiDou-3 Navigation Satellite System Precise Point Positioning (PPP-B2b) services and employing PPP technology as the primary positioning method. The positioning enhancement service is provided by the Assisted Global Navigation Satellite System (A-GNSS) location platform developed by the China Academy of Information and Communications Technology. The signaling interaction between the server and the users strictly adheres to the Third Generation of Mobile Communications Technology Partnership Project Long-Term Evolution Positioning Protocol and the Open Mobile Alliance Secure User Plane Location framework. To comprehensively evaluate the Redmi K60 Ultra’s capabilities, this study designed six distinct experimental scenarios and conducted comprehensive research on multi-frequency and multi-GNSS observation noise, Time to First Fix (TTFF), as well as the performance of both GNSS-based and network-based positioning. Experimental results indicate that the GNSS chipset within the Redmi K60 Ultra has achieved a leading position in the consumer market concerning supported satellite constellations, frequencies, and observation accuracy, and is comparable to some low-cost GNSS receivers. A-GNSS positioning can reduce the TTFF from 30 to under 5 s, representing an improvement of over 85% in the cold start speed compared to a standalone GNSS mode. The positioning results show that the A-GNSS PPP-B2b service can achieve positioning performance with RMS errors of less than 1.5 m, 2.5 m, and 4 m in open-sky, realistic, and challenging urban environments. Compared to GNSS-based positioning, cellular network-based Observed Time Difference of Arrival (OTDOA) positioning achieves an accuracy ranging from tens to hundreds of meters in various experimental scenarios and currently functions primarily as coarse location determination. Additionally, this study explores the potential of the Three-Dimensional Mapping-Aided (3DMA) GNSS algorithm in detecting Non-Line-of-Sight signals and enhancing positioning performance. The results indicate that 3DMA PPP, as compared to conventional PPP, can significantly accelerate PPP convergence and improve positioning accuracy by over 30%. Consequently, 3D city models can be utilized as future assistance data for the A-GNSS location platform.

Cognitive Resource Analyzer for Cellular Network Ecosystems

Modern cellular infrastructure has grown in complexity and become an ecosystem that includes the host technologies, such as 4G Long Term Evolution (LTE) and 5G New Radio (NR), along with subsystems such as narrowband Internet of Things (NB-IoT), category M1 (Cat-M1/LTE-M), observed time difference of arrival (OTDOA) and support for 4G/5G coexistence using dynamic spectrum sharing (DSS). Such an increased complexity has driven the need for network monitoring to enable load tracking, congestion control, spectral efficiency analysis, intrusion detection, and cognitive radio communications. However, no approach can passively monitor the entire cellular ecosystem because some reservations are configured with high-layer messages that are only accessible to in-network, active, and sometimes user-specific equipment. In this work, we design the Resource Analyzer for Variable Ecosystem Networks (RAVEN) to monitor the individual technologies within the cellular ecosystem. RAVEN reduces the synchronization search space for multiple subsystems and enables a fine-grained subsystem-level tracking of spectrum usage. RAVEN also provides a method to detect anomalies and find subsystems that are not yet supported. RAVEN is validated through simulation and live experiments and is compared to other cellular network monitors.

A Novel Time Delay Estimation Algorithm for 5G Vehicle Positioning in Urban Canyon Environments.

Vehicle positioning with 5G can effectively compensate for the lack of vehicle positioning based on GNSS (Global Navigation Satellite System) in urban canyons. However, there is also a large ranging error in the non-line of sight (NLOS) propagation of 5G. Aiming to solve this problem, we consider a new time delay estimation algorithm called non-line of sight cancellation multiple signal classification (NC-MUSIC). This algorithm uses cross-correlation to identify and cancel the NLOS signal. Then, an unsupervised multipath estimation method is used to estimate the number of multipaths and extract the noise subspace. The MUSIC spectral function can be calculated by the noise subspace. Finally, the time delay of the direct path is estimated by searching the peak of MUSIC spectral function. This paper adopts the 5G channel model developed by 3GPP TR38.901 for simulation experiments. The experiment results demonstrated that the proposed algorithm has obvious advantages in terms of NLOS propagation for urban canyon environments. It provided a high-precision time delay estimation algorithm for observed time difference of arrival (OTDOA), joint angle of arrival (AOA) ranging, and other positioning methods in the 5G vehicle positioning method, which can effectively improve the positioning accuracy of 5G vehicle positioning in urban canyon environments.

Observed time difference of arrival based position estimation for LTE systems: simulation framework and performance evaluation

Precise user equipment (UE) location is paramount for the reliable operation of location-based services provided by mobile network operators and other emerging applications. In this paper, the Long Term Evolution (LTE) network positioning performance based on mobile assist Observed Time Difference of Arrival (OTDoA) method is considered. The received signal time difference (RSTD) measurements are estimated by the UE using dedicated position reference signal (PRS) transmitted in the downlink frame where the reported time measurements are used by the network for location calculation. A simulation framework for the position estimation in LTE networks is presented where the LTE downlink communication link is implemented. The correlation-based method for the time of arrival measurement is used for the implementation of OTDoA. The simulation framework provides different configurations and adjustments for the system and network parameters for evaluating the performance of LTE positioning using OTDoA over multipath fading channels. Different simulation scenarios are conducted to identify the influence of various parameters of LTE system and positioning procedure setup on the positioning accuracy. Simulation results demonstrated that the positioning accuracy is highly affected by the channel fading condition where the accuracy of time of arrival measurements is deteriorated in severe fading environments; however, the positioning accuracy can be significantly improved by increasing the positioning sequences involved in the estimation process either in the frequency domain or in the time domain.

Detection of the First Component of the Received LTE Signal in the OTDoA Method

In a modern world there is a growing demand for localization services of various kinds. Position estimation can be realized via cellular networks, especially in the currently widely deployed LTE (Long Term Evolution) networks. However, it is not an easy task in harsh propagation conditions which often occur in dense urban environments. Recently, time-methods of terminal localization within the network have been the focus of attention, with the OTDoA (Observed Time Difference of Arrival) method in particular. One of the main factors influencing the accuracy of location estimation in the OTDoA method is the nature of the propagation channel that affects the ease of isolating the signal component travelling from the transmitter to the receiver through the shortest path. To obtain the smallest possible localization error, it is necessary to detect the first received component of the useful signal. This aim could be achieved by using a proper algorithm within the receiver. This paper proposes a new algorithm for effective detecting of the first component of the LTE downlink signal in the multipath environment. In a mobile terminal location estimation process, CSRS (Cell Specific Reference Signal) signals were used instead of dedicated PRS (Positioning Reference Signal) signals. New solution was verified during the measurement campaign in a real LTE network.

A Comparative Study between Iterative Algorithms for TDOA Based Geolocation Techniques in Real UMTS Networks

In this paper, we analyze the Observed Time Difference of Arrival (OTDOA) technique to simultaneously estimate the position of the different user equipments and the relative time difference between Node Bs in real UMTS networks. We concentrate on comparing two methods to solve the nonlinear system of equations, the well-known Gauss-Newton and the Levenberg-Marquardt algorithm. We show this latter method offers better results, providing faster convergence, higher accuracy and more robustness. Finally, a modification to the classical Levenberg-Marquardt algorithm is proposed in order to avoid divergences in that method.

Three-Dimensional Positioning for LTE Systems

In the Third-Generation Partnership Project (3GPP) Long-Term Evolution (LTE) specifications, several 2-D positioning methods have been proposed to support location-based services (LBSs). It has been shown that the observed time difference of arrival (OTDOA) method provides the best result. With the advent of the fifth-generation cellular systems, 3-D beamforming will be introduced, and 2-D positioning may not be sufficient for future applications. Although the conventional OTDOA method can be used in 3-D positioning, it requires more base stations (BSs) in cooperation and often performs poorly in typical cellular network geometry. In this paper, we propose a novel OTDOA-based method to solve the problems. First, we exploit the sparsity of the wireless channel and propose to use a compressive-sampling-based channel estimation method, which greatly enhances the precision of time-of-arrival (TOA) estimation. Then, we propose a transmit beamforming scheme such that the elevation angle of departure (AOD) can be accurately estimated. Finally, we combine the estimated TOAs and the AOD in the OTDOA scheme to conduct 3-D positioning. With the proposed scheme, the number of BSs required for 3-D positioning remains the same as that of 2-D, and the positioning accuracy greatly outperforms that of the conventional OTDOA method. Simulations show that 90% of the position error can be less than 7 m.

Error Analysis of the OTDOA From the Resolved First Arrival Path in LTE

The accuracy of the observed time difference of arrival (OTDOA) in the long-term evolution (LTE) systems depends on the accuracy of the time of arrival (TOA) measurements, which are often corrupted by various errors caused by non-light-of-sight propagation, multipath interference, noise, and path detection techniques. Furthermore, signal bandwidth, channel condition, distance from the evolved node-B, and scatterer distribution are the affecting parameters on the OTDOA accuracy. Since the user equipment obtains the most accurate TOA from the resolved first arrival path (R-FAP), understanding errors of the TOA and OTDOA from the R-FAP is necessary to develop OTDOA positioning techniques. In this paper, we develop theoretical expressions for the TOA and OTDOA error distributions of the R-FAP for outdoor multipath environments by integrating theoretical models of the errors expressed with the affecting parameters, and theoretical expressions are verified with numerous Monte Carlo simulations. In addition, we propose an LTE OTDOA positioning technique that compensates the mean TOA offset in the TDOA measurements before applying a positioning algorithm, and we demonstrate the performance improvement using Monte Carlo simulations. In this paper, we do not include OTDOA errors due to the network synchronization and intercell interference.

An Enhanced Observed Time Difference of Arrival Based Positioning Method for 3GPP LTE System

In 3GPP (3-rd Generation Partnership Project) LTE (Long Term Evolution) system, the use of PRS (Positioning Reference Signal) for OTDOA (Observed Time Difference of Arrival) based positioning method has been agreed. However, PRSs can be overlapped at the receiver side in synchronous network because the frequency shift pattern of PRS is decided by cell ID (Identity). Moreover, in asynchronous network, the loss of orthogonality between received PRSs generates continuous interferences. Even though autonomous muting can be applied to solve the interference problems in synchronous and asynchronous networks, the muting scheme degrades the overall positioning efficiency and requires additional network complexity. Therefore, in this paper, we propose novel OTDOA based positioning methods at the receiver side to improve positioning efficiency: cancellation method of serving PRS for synchronous network, TDORS (Time Domain Orthogonal Reference Signal) generation and useful CIR (Channel Impulse Response) selection methods for asynchronous network. We verified that the proposed methods can achieve an accurate estimation and stable operation without PRS muting.

Mobile terminal location for UMTS

Interest in mobile phone location is expanding due to the implementation of the third generation (3G) multimedia phones. The initial need for accurate terminal positioning has been motivated by government authorities, mainly by the US FCC's E911 mandate for emergency services. In Europe, similar ideas have appeared but the primary interest is in commercial value-added functions. Systems resembling air navigation and secondary radar as brought down to street level and pedestrian speeds are also foreseen. This article presents an overview of UMTS mobile terminal location. The performance of standardized observed time difference of arrival (OTDOA) and a novel database correlation method (DCM) for wide bandwidth systems are evaluated through simulations in an urban microcell environment. DCM is shown to provide a reasonable location error of 25 m for 67% of the calls. The obtained respective OTDOA accuracy is 215 m only. Location problems encountered in built-up areas and relevant applications based on the obtained accuracy are discussed.