1,720,964 research outputs found
Time of arrival estimation of LTE signals for positioning: bounds and algorithms
No full textThis thesis presents a research work on the estimation of the time of arrival (TOA) of modern cellular signals for positioning purposes. The Third Generation Partnership Project (3GPP) Long Term Evolution (LTE) signals are analyzed, and the underlying orthogonal frequency division multiplexing (OFDM) based physical layer used in the cellular downlink is exploited. The original contribution presented in the thesis is twofold.
Firstly, a framework has been developed for assessing the TOA estimation performance achievable with OFDM signals. The signals are realistically modeled, and different power distributions of the available OFDM sub-carriers have been carefully defined. This allowed new exploration of the TOA estimation performance both in the asymptotic and in the threshold root mean square error (RMSE) regions. Moreover, a novel performance metric based on the shape of the Ziv-Zakai bound curve has been defined, and used to precisely evaluate the boundaries between the threshold and asymptotic RMSE regions. The analysis revealed a trade-off between the threshold RMSE, which is related in practice to
sensitivity, and the asymptotic RMSE, which determines the ultimate accuracy.
This shows that not only the Gabor bandwidth but also the threshold signal-to-noise ratio (SNR) should be considered when designing reference signals.
Secondly, a TOA estimation algorithm has been developed and applied to real LTE OFDM signals collected in multipath indoor and outdoor propagation environments. The new algorithm, referred to as ESPRIT and Kalman filter
for time of Arrival Tracking (EKAT), combines a super-resolution algorithm,
which performs the multipath separation, with a Kalman filter, which tracks the estimated direct path TOA. In addition, techniques have been extended for combining the received LTE pilot tones in the time, frequency, spatial and also cell ID domains. This exploits the intrinsic diversity offered by the LTE cell specific reference signal (CRS), and showed an improvement in the robustness and in the quality of the TOA estimates. The pseudoranges evaluated with the proposed EKAT algorithm have been used to feed a positioning filter, delivering
position estimates with an error smaller than 8 m (50% CEP) in the indoor
scenario
Design criteria and genetic algorithm aided optimization of three-stage-concatenated space-time shift keying systems
No full textThe Space-Time Shift Keying (STSK) framework subsumes diverse Multiple-Input Multiple-Output (MIMO) schemes, offering a near-capacity performance at a reduced complexity. The STSK system’s performance crucially depends on the dispersion matrix (DM) set used for encoding the transmitted symbols. We introduce a novel criterion, based on EXtrinsic Information Transfer (EXIT) chart analysis, for selecting capacity-approaching sets from candidate DMs, and a novel Genetic Algorithm (GA) for efficiently exploring the search space formed by the candidate DM sets. Our proposed GA allows obtaining DM sets that enhance the system’s performance compared to a random selection, while simultaneously reducing the search algorithm’s complexity.<br/
Performance analysis of time of arrival estimation on OFDM signals
Full text linkThis letter characterizes the error performance of realistically modelled orthogonal frequency division multiplexing (OFDM) signals, when their time of arrival has to be estimated in an additive white Gaussian noise channel. In particular, different power distributions on the available sub-carriers of the OFDM signal are considered, and bounds on the corresponding root mean square estimation error (RMSEE) are evaluated. The tools used for such purpose are the widely adopted Cramér-Rao bound and the Ziv-Zakai bound, which is tight in a wide range of signal-to-noise ratio (SNR) values. The presented analysis reveals that, for a given signal bandwidth, a proper power distribution on the OFDM sub-carriers is crucial for achieving a good performance in the low to medium SNR region, where the RMSEE curve exhibits the typical threshold behavior. Moreover, a trade-off between asymptotic and threshold performance is identified, thanks to the adoption of a novel performance figure, which directly describes the threshold RMSEE behavior
Positioning Using LTE Signals
No full textGNSS is excellent in open-sky conditions, but in many everyday situations such as traveling in urban canyons or being inside buildings, too few GNSS space vehicles (SV) are visible to get a position fix. An alternative is then desirable, and can be provided by positioning using the signals from cellular base stations. Of particular interest are the new signals and positioning possibilities from LTE cellular network operators, since the LTE coverage is expected to be high in cities and other well-populated areas. Furthermore, to accommodate the need for increasing data rates network operators are configuring their LTE downlink bandwidth to be as wide as possible, providing good resolution of different multipath components, which also assists positioning. A portable experimental setup was built to perform measurements and to gather knowledge about the overall performance of positioning with LTE signals. It consists of a universal software radio peripheral (USRP) N210 that is synchronized to a GPS-locked Rubidium frequency standard. A personal computer (PC) acts as an overall system controller and as a recording unit, storing LTE data samples together with GNSS sentences from a u-blox LEA-6T module. A Matlab-based algorithm does the complete post-processing, extracting pseudoranges for the LTE BS, and calculating the position solution.The results of determining the position of a car driven on a route around the town of Rapperswil, Switzerland show the potential of the positioning approach, using only available LTE signals. Even with the basic system the root meansquare (RMS) value of the absolute error in a position using LTE compared to the actual position using GPS is 43 m, demonstrating that the CRS signal of the LTE standard is well suited as a fall-back alternative to GNSS in environmentally challenging situations
Vehicular Position Tracking Using LTE Signals
Full text linkThis paper proposes and validates, in the field, an approach for position tracking that is based on Long-Term Evolution (LTE) downlink signal measurements. A setup for real data live gathering is used to collect LTE signals while driving a car in the town of Rapperswil, Switzerland. The collected data are then processed to extract the received LTE cell-specific reference signals (CRSs), which are exploited for estimating pseudoranges. More precisely, the pseudoranges are evaluated by using the “ESPRIT and Kalman Filter for Time-of-Arrival Tracking” (EKAT) algorithm and by taking advantage of signal combining in the time, frequency, spatial, and cell ID domains. Finally, the pseudoranges are corrected for base station's clock bias and drift, which are previously estimated, and are used in a positioning filter. The obtained results demonstrate the feasibility of a position tracking system based on the reception of LTE downlink signals
Discrete-time simulation of smart antenna systems in Network Simulator-2 Using MATLAB and Octave
No full textA simple method for TOA estimation in OFDM systems
No full textIn this paper a simple algorithm for the estimation of the Direct Path (DP) Time of Arrival (TOA) in an OFDM-based telecommunications system is proposed. It is shown that, under certain conditions, it is possible to infer the TOA of the direct path by estimating the phase slope across the subcarriers. The proposed algorithm exploits the intrinsic properties of a multi-carrier OFDM system to perform the estimation, and it can be employed in a fully opportunistic way if known reference signals (intended for purposes other than TOA estimation) are available. The obtained TOA estimations can be used to calculate the pseudo-ranges that can be employed for trilateration-based positioning. The performance of the proposed algorithm and its variants are assessed with simulations
Estimation and tracking of LTE signals time of arrival in a mobile multipath environment
No full textThis paper proposes an algorithm for the estimation and tracking of the direct path (DP) time of arrival (TOA) of the signals received from 4G long term evolution (LTE) cellular base stations (BSs) in a mobile multipath environment. This is important for TOA-based ranging measurements, which may be exploited for positioning applications. A sub-space approach is used for the estimation of the multipath time of arrival, and a state-space approach is exploited for tracking the direct path. The developed framework is applied to real LTE signals collected
using a portable experimental setup during a car drive in the town of Rapperswil, Switzerland. The pseudoranges derived from the tracking of the DP TOA are then compared to the ranges from the considered LTE base stations calculated using GPS, demonstrating the effectiveness of the proposed approach
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