Software-only TDOA/RTF positioning for 3G WCDMA wireless network

A hybrid location finding technique based oil time difference of arrival (TDOA) with round-trip time (RTT) measurements is proposed for a wideband code division Multiple access (WCDMA) network. In this technique, a mobile station measures timing from at least three base stations using user equipment receive-transmit (UE Rx-Tx) time difference and at least three base stations measure timing from the mobile station using RTT. The timing measurements of mobile and base stations are then combined to solve for both the location of the mobile and the synchronization offset between base stations. A software-only geolocation system based on the above mobile/base stations timing measurements is implemented in Matlab platform and the performance of the system is investigated using large-scale propagation models

MmWave V2V Localization in MU-MIMO Hybrid Beamforming

Recent trends for vehicular localization in millimetre-wave (mmWave) channels include employing a combination of parameters such as angle of arrival (AOA), angle of departure (AOD), and time of arrival (TOA) of the transmitted/received signals. These parameters are challenging to estimate, which along with the scattering and random nature of mmWave channels, and vehicle mobility lead to errors in localization. To circumvent these challenges, this paper proposes mmWave vehicular localization employing difference of arrival for time and frequency, with multiuser (MU) multiple-input-multiple-output (MIMO) hybrid beamforming; rather than relying on AOD/AOA/TOA estimates. The vehicular localization can exploit the number of vehicles present, as an increase in a number of vehicles reduces the Cramr-Rao bound (CRB) of error estimation. At 10 dB signal-to-noise ratio (SNR) both spatial multiplexing and beamforming result in comparable localization errors. At lower SNR values, spatial multiplexing leads to larger errors compared to beamforming due to formation of spurious peaks in the cross ambiguity function. Accuracy of the estimated parameters is improved by employing an extended Kalman filter leading to a root mean square (RMS) localization error of approximately 6.3 meters

mmWave V2V Localization in MU-MIMO Hybrid Beamforming

Recent trends for vehicular localization in millimetre-wave (mmWave) channels include employing a combination of parameters such as angle of arrival (AOA), angle of departure (AOD), and time of arrival (TOA) of the transmitted/received signals. These parameters are challenging to estimate, which along with the scattering and random nature of mmWave channels, and vehicle mobility lead to errors in localization. To circumvent these challenges, this paper proposes mmWave vehicular localization employing difference of arrival for time and frequency, with multiuser (MU) multiple-input-multiple-output (MIMO) hybrid beamforming; rather than relying on AOD/AOA/TOA estimates. The vehicular localization can exploit the number of vehicles present, as an increase in a number of vehicles reduces the Cramr-Rao bound (CRB) of error estimation. At 10 dB signal-to-noise ratio (SNR) both spatial multiplexing and beamforming result in comparable localization errors. At lower SNR values, spatial multiplexing leads to larger errors compared to beamforming due to formation of spurious peaks in the cross ambiguity function. Accuracy of the estimated parameters is improved by employing an extended Kalman filter leading to a root mean square (RMS) localization error of approximately 6.3 meters

Cramer-Rao bounds in the estimation of time of arrival in fading channels

This paper computes the Cramer-Rao bounds for the time of arrival estimation in a multipath Rice and Rayleigh fading scenario, conditioned to the previous estimation of a set of propagation channels, since these channel estimates (correlation between received signal and the pilot sequence) are sufficient statistics in the estimation of delays. Furthermore, channel estimation is a constitutive block in receivers, so we can take advantage of this information to improve timing estimation by using time and space diversity. The received signal is modeled as coming from a scattering environment that disperses the signal both in space and time. Spatial scattering is modeled with a Gaussian distribution and temporal dispersion as an exponential random variable. The impact of the sampling rate, the roll-off factor, the spatial and temporal correlation among channel estimates, the number of channel estimates, and the use of multiple sensors in the antenna at the receiver is studied and related to the mobile subscriber positioning issue. To our knowledge, this model is the only one of its kind as a result of the relationship between the space-time diversity and the accuracy of the timing estimation.Peer ReviewedPostprint (published version

Techniques for Mobile Location Estimation in UMTS

The subject area of this thesis is the locating of mobile users using the future 3rd generation spread spectrum communication system UMTS. The motivation behind this work is twofold: firstly the United States Federal Communications Commission (FCC) mandated the provision of user location into services in the United States of America due to the increasing number of emergency calls originating from unknown locations. Secondly the user location can enable a number of other potentially profit–making applications and services. These are generally thought to be the important new applications of the third generation mobile networks. The UMTS standard has now made provision for a time difference of arrival based mobile user location system in which the mobile measures time differences of arrival of received signals from surrounding base stations (BS’s). There are two main problems to such a technique: firstly the problem of detecting enough base stations to make a location fix, the so called ‘hearability’ problem. In spread spectrum systems all base stations transmit on the same bandwidth thus non–serving BS’s may not be detectable in normal operation. The second problem is non–line of sight (NLOS) propagation, in which time difference measurements (or any other measurement types) may be corrupted significantly, thus causing significant location error. The thesis of this work is that these two problems can be entirely overcome using spatial filtering of measurements and location estimates. Two constraints that are placed on the filtering algorithms are that the operation should be real time and that the precise distribution of NLOS errors is unknown (though certain key characteristics are exploited). A channel model is first developed, which specifically characterises line of sight and NLOS transitions as well as out of cell radio wave propagation. Several scenarios are then simulated. Slow moving users, low hearability and heavily NLOS conditions pose the biggest challenge. Spatial filtering is achieved by Kalman filters adapted to the problem, as well as simple averaging filters. Results show that improved location accuracy (to within FCC recommendations) is possible in all considered scenarios with spatial filtering as well as improved robustness to low hearability. The detection stage of the receiver is also analysed in detail and methods to improve hearability are presented. The performance of a hybrid location system using angle of arrival measurements of the mobile at the serving BS is also assessed. A fairly pessimistic model for the spread of NLOS errors is used, however significant location improvement is noted in several scenarios. Worst performance occurs in urban scenarios so finally a novel approach to user location is described which is robust to NLOS propagation conditions and also overcomes the hearability problem since only measurements at the serving BS are required. The technique, termed Scatterer Back Tracing (SBT), uses and requires multipaths to calculate the mobile location. Results suggest this SBT can provide extremely high location accuracy but is very sensitive to measurement noise