[Show abstract][Hide abstract] ABSTRACT: We envisage a very high mobile terminal (MT) density for future wireless networks which requires ubiquitous high-definition network self-localization ability. Traditional network localization contains two steps: ranging and localization. The coherence between the two steps is not fully exploited. We propose a direct signal domain particle filter for network self-localization (DiPLoc). The key objective is to obtain the location information directly from the received signal samples, i.e. the waveform, avoiding hard decision in the intermediate step and the ranging model approximation. The complexity of the proposed DiPLoc is similar to the two-step approach. Both of the numerical and experimental results show that, the DiPLoc outperforms the traditional two-step approaches especially when the network is dense.
[Show abstract][Hide abstract] ABSTRACT: To investigate the broadband over sea wave propagation channel for communication and navigation applications, the German Aerospace Center conducted a broadband channel sounder measurements where the transmit antenna was mounted on a ship and the receive antenna was located on the land. Using this setup, measurements were performed for C-band at 5.2GHz with a broadband signal of 100MHz bandwidth. Results are given in terms of receiver height dependent power delay profile, delay spread and mean delay.
[Show abstract][Hide abstract] ABSTRACT: In the wireless channel, a signal propagates from the transmitter to the receiver along certain geometrical paths. Along each path, interactions between the signal and physical objects may occur. According to distinct interaction phenomena, different models of individual multipath components (MPCs) are needed for accurate simulations of propagation affects. In this paper, we consider MPCs due to reflection, scattering and combinations of both. Three types of MPCs are individually defined and modeled. Based on channel measurement data, the characteristics of each different type of MPC is presented in this paper.
[Show abstract][Hide abstract] ABSTRACT: Positioning is next to communication the most important field of applications for wireless radio transmissions. This paper considers indoor positioning using wireless signals. Especially in indoor scenarios, multipath reception degrades the accuracy of the positioning device as long as the receiver is based on standard methods. Strategies to mitigate multipath effects on range estimates are in general based on the estimation of the channel impulse response (CIR). All these methods have in common that they determine the CIR in order to remove the influence on the estimate of the line-of-sight path delay. This paper focuses on multipath aided positioning by using the time difference of arrival between multipath components (TDoAbMC). Hence, the paper uses the multipath propagation of the wireless signal to allow positioning in cases of a insufficient number of transmitters or increase the accuracy otherwise. Measurements with a moving receive antenna showed, that multipath components are visible for several meters of receiver movement. To estimate and track the time-variant multipath components of the received signal, the paper uses a Kalman filter which utilizes maximum likelihood estimates as measurements. For positioning, the novel approach treats multipath components as signals from virtual transmitters which are time synchronized to the physical transmitter and fixed in their position. Additionally, using a time difference of arrival approach, the estimation of the user clock bias is not necessary. To use the information of the multipath components, the positioning algorithm has to estimate the user position and the position of the virtual transmitters simultaneously. Furthermore, the new approach does not rely on any prior information such as the room layout or a database for fingerprinting.
[Show abstract][Hide abstract] ABSTRACT: In spread-spectrum navigation systems, the positioning error (or tracking accuracy) is determined from the jitter deviation of delay-locked loops (DLLs). However, jitter simulations are computationally complex, and conventional analytical methods provide only unsatisfactory and incomplete jitter results. Thus, our contribution presents a novel method for the analytical jitter computation by mapping the stochastic differential equation (SDE) of the DLL onto an Ornstein–Uhlenbeck (OU) SDE. Its solution is the well-known OU random process, which is a time-variant Gaussian distribution. The expectation value and the variance of the OU random process yield the jitter deviation. Thus, we derive the analytical time-variant jitter function with its transient response, which was to date unavailable. Contrary to previous jitter computations based on a loop transfer function, our method covers DLLs of any order. We obtain the loop parameters that minimise the jitter deviation analytically without computationally complex simulations. Above all, our method based on OU random processes enables for the first time an efficient joint analytical mean time to lose lock (MTLL) and jitter computation. Therefore, both computationally complex MTLL and jitter simulations become obsolete for many kinds of DLLs
No preview · Article · Dec 2012 · Transactions on Emerging Telecommunications Technologies
[Show abstract][Hide abstract] ABSTRACT: This paper presents a novel method for the analytical mean time to lose lock (MTLL) computation of coherent second-order Langevin delay-locked loops (DLLs). Analytical MTLL computation is a key task for DLLs, since the computational complexity of numerical MTLL simulations is far too high in many operating ranges of the second-order Langevin DLLs. To obtain the crucial MTLL values analytically without simulations, we rewrite the Langevin stochastic differential equation (SDE) as a vector-valued Ornstein-Uhlenbeck (OU) SDE. It includes a Gaussian noise term, which yields as a solution of the vector-valued OU SDE a time-variant Gaussian distribution. Thus, the complementary error function yields the loss of lock probability and thereby the MTLL. If we replace the complementary error functions by suitable exponential approximations, we obtain a simple MTLL expression with an exponential function as dominant term. The simple exponential MTLL expression yields the optimum loop parameters corresponding to the maximum MTLL. Simulation results confirm that the optimum loop parameters corresponding to our analytical MTLL computation method and to the simplified exponential approximation coincide. Besides the crucial analytical MTLL results, the OU random processes yield additionally the likewise crucial analytical jitter results.
No preview · Article · Nov 2012 · IEEE Transactions on Communications
[Show abstract][Hide abstract] ABSTRACT: Global navigation satellite systems (GNSSs) can deliver very good position estimates under optimum conditions. However, especially in urban canyons and indoor scenarios with severe multipath propagation and blocking of satellites by buildings the accuracy loss can be very large. Often, positioning with GNSSs is impossible in these scenarios. On the other hand, cellular wireless communication systems such as the third generation partnership project (3GPP) long-term evolution (LTE) provide excellent coverage in urban and most indoor environments. Thus, this paper researches timing based positioning algorithms, in this case time difference of arrival (TDoA), using 3GPP-LTE and GPS measurements. This paper considers a particle filter for 3GPP-LTE TDoA positioning and the fusion of 3GPP-LTE signals with GPS measurements. To obtain better positioning results, a 3GPP-LTE TDoA error model is derived, which splits the TDoA errors in slow varying and fast varying errors. The slow varying error model is included in the prediction model and the fast varying error model in the likelihood function of the particle filter. The last part of this paper, evaluates the positioning performances of the developed particle filter in an indoor scenario. These evaluations show clearly the possibility of using 3GPP-LTE measurements for indoor positioning. Additionally, it shows the advantage of fusing 3GPP-LTE with GPS measurements.
[Show abstract][Hide abstract] ABSTRACT: Services and applications based on accurate knowledge of the mobile terminal (MT) location play a fundamental role in current and future wireless communications systems. In addition, the United States Federal Communications Commission (FCC) has stated accuracy requirements on the location determination process of enhanced 911 (E-911) emergency callers. Global navigation satellites systems (GNSSs) based positioning provides a sufficient accuracy in rural and suburban environments, where a sufficient number of satellites are visible in line-of-sight conditions. However, in GNSS critical environments, such as dense urban, urban canyon or even indoors, view to sky is limited. In these environments, low signal power, bad satellite constellations, severe multipath and non-line-of-sight propagation causes erroneous and biased position estimates. Especially in these environments, cellular wireless communication systems provide good coverage and can be used for position determination of the MT. Mobile radio communications systems like GSM, UMTS or the currently deployed 3GPP-LTE primarily target on optimizing communication performance figures such as bandwidth efficiency or data throughput. Availability, signal strength or even signal bandwidths, however, make them interesting for positioning. However, the correlation properties of the synchronization signals of the 3GPP LTE system limit the positioning performances. Moreover, while non-line-of-sight propagation improves the communication performance, it degrades the navigation performance due to the additional distance the signal might travel.
Hence, this paper shows an indoor positioning approach with the 3GPP-LTE mobile communication standard, which is currently deployed in many countries. Moreover, it shows the benefit of using the 3GPP-LTE mobile communication system for indoor positioning. Therefore, this paper describes a novel real-time mobile radio based positioning system using time-difference-of-arrival (TDOA) measurements. The paper considers an indoor scenario, where the transmitters are located outdoors and the MT is moving in an office building. The position estimation is done by a particle filter. Furthermore, to improve the positioning accuracy, this paper derives a time-variant error model for indoor positioning. Using this time-variant error model, the positioning error of the MT can be decreased significantly.
The downlink of 3GPP-LTE is based on Orthogonal Frequency Division Multiplexing (OFDM), which allows a spectral efficient and flexible usage of the available frequency spectrum. The 3GPP-LTE standard specifies signal parts, dedicated to time and frequency synchronization. For our investigations we use these synchronization signals for TDOA based position estimation. The 3GPP-LTE signal structure, in particular the properties of the synchronization properties, will be discussed in detail in the final paper.
For the 3GPP-LTE positioning we apply a particle filter in order to process TDOA measurements of the 3GPP-LTE base stations. The TDOA measurements are taken from DLR´s 3GPP-LTE positioning test-bed. The test-bed consists of up to four synchronous transmitters. From each transmitter site a predefined 3GPP-LTE OFDM frame can be transmitted periodically. The test-bed operates at 2.4 - 2.5 GHz, providing signal bandwidths of up to 20 MHz. At the receiver we convert the received signal down to base band and sample both the inphase and quadrature component. The sampled signal is stored on a hard disk, which allows both offline and real-time processing.
These sampled data are processed by the TDOA estimation algorithm and consists of two steps. The first step estimates the TDOA roughly by correlating the narrow band synchronization signals with the received sequence and the second step performs subsample based estimation with the wideband pilot symbols. These algorithms use a first peak and maximum peak detection algorithms, for detecting the first and maximum arriving signal. However, the 20 MHz bandwidth limits the rough synchronization and allows only a sample based estimation within 15 meters, which hinders accurate positioning in indoor environments. Thus, an oversampling approach is used, to tackle this issue which results in a significant error reduction.
However, due to hardware imperfections of the test-bed and channel errors, such as non-line-of-sight and multipath propagation, the TDOA measurements are noisy and biased. Thus, to obtain better positioning results, this bias has to be predicted and mitigated. Several approaches exist to model time of arrival based ranging in indoor environments. All of these statistical models depend on bandwidth, carrier frequency and are time-invariant. However, for navigation applications an evaluation of the multipath and non-line-of-sight error for a moving receiver is essential. Hence, to improve the positioning accuracy, we derive in this paper a time-variant TDOA error model based on a measurement campaign of an outdoor-to-indoor channel. The evaluation of this measurement campaign yields an autoregressive error model which allows us to predict the TDOA error for a moving MT.
By using this model within the particle filter yields promising results in terms of error mitigation. Each particle itself models the multipath and non-line-of-sight error according to the obtained time-variant error model. Additionally, we compare these results to the more general approach by assuming an uncorrelated error.
In the final paper, we will provide a detailed description of the 3GPP-LTE downlink signal structure, which we use for TDOA based positioning. We will discuss and describe the applied algorithms for timing (pseudo-range) estimation. Furthermore, we will describe the 3GPP-LTE test-bed and the scenario in detail. Additionally, the particle filter used for the positioning estimation will be described in detail. Especially, we will analyze the measurement results and the derived time-variant model to predict and mitigate the multipath and non-line-of-sight error in the particle filter.
[Show abstract][Hide abstract] ABSTRACT: Orthogonal frequency division multiplexing (OFDM) became a popular transmission approach since it suppresses intersymbol interference (ISI) due to large channel delays. However, intercarrier interference (ICI) for high mobility receivers yields corrupted channel estimates for pilot-aided OFDM channel estimation. Thus, this paper presents a novel time-variant channel estimation approach to mitigate this system impairment. We linearize the time-variant channel and determine the expansion point by channel estimates corresponding to the current OFDM symbol, and we get the unknown channel slopes by an iterative data and channel estimation. Our algorithm combines a least squares or a minimum norm channel slope estimation and the detection of the channel paths. It sets any channel path power equal zero once the corresponding power estimate is smaller than a given threshold. Our algorithm exploits the large channel correlations between the cyclic prefix and the successive OFDM symbol optimally. These maximum correlations reason the superiority of ICI mitigation with cyclic prefixes compared to channel slope estimation with adjacent OFDM symbols, which needs at least twice the number of pilot symbols. Additionally, our iterative ICI mitigation reduces noise impairments.
[Show abstract][Hide abstract] ABSTRACT: Global navigation satellite systems (GNSSs) can deliver very good position estimates under optimum conditions. However, in urban and indoor scenarios positioning with GNSS is often impossible. On the other hand, cellular wireless communication systems, e.g., the new, orthogonal frequency division multiplexing (OFDM) based third generation partnership project’s
long-term evolution (3GPP-LTE), provide excellent coverage in
urban and most indoor environments. Thus, this paper researches timing based positioning algorithms for OFDM using time difference of arrival (TDOA) measurements and the 3GPP-LTE signals. Therefore, it introduces synchronization, TDOA estimation, and signal–to–noise ratio (SNR) estimation algorithms. To solve the navigation equation for TDOA, this paper considers the static Gauss-Newton algorithm, positioning Kalman filter and particle filter. Further, this paper derives new Cram´er-Rao lower bounds (CRLBs) to analyze the obtained algorithms. First, new CRLBs are derived for TDOA estimation and pairwise synchronized or fully synchronized transmitters. Afterwards, static and novel dynamic recursive Bayesian CRLBs are derived for position estimation. The CRLBs are compared to real estimated TDOAs and positions. Improvements of the positioning algorithms are still possible compared to the CRLBs. Nevertheless, this paper demonstrates that indoor positioning with TDOAs from OFDM based on 3GPP-LTE is possible.
[Show abstract][Hide abstract] ABSTRACT: The key step of syndrome-based decoding of Reed-Solomon codes up to half the minimum distance is to solve the so-called Key Equation. List decoding algorithms, capable of decoding beyond half the minimum distance, are based on interpolation and factorization of multivariate polynomials. This article provides a link between syndrome-based decoding approaches based on Key Equations and the interpolation-based list decoding algorithms of Guruswami and Sudan for Reed-Solomon codes. The original interpolation conditions of Guruswami and Sudan for Reed-Solomon codes are reformulated in terms of a set of Key Equations. These equations provide a structured homogeneous linear system of equations of Block-Hankel form, that can be solved by an adaption of the Fundamental Iterative Algorithm. For an (n,k) Reed-Solomon code, a multiplicity s and a list size l , our algorithm has time complexity O(ls4n2).
Full-text · Article · Sep 2011 · IEEE Transactions on Information Theory
[Show abstract][Hide abstract] ABSTRACT: Indoor positioning is an extremely challenging task for GNSS positioning. Thus, we propose to use terrestrial communications systems such as 3GPP-LTE as a complementary positioning system. We estimate the expected positioning performance of 3GPP-LTE indoor positioning by assessing link budgets and calculating the Cram´er-Rao lower bounds for pseudo-range and 2D position estimation. An experiment shows that the combination of mobile radio based positioning can achieve a positioning accuracy in the range of a few meters, indicating that such technologies are suitable for complementing GNSS indoors.
[Show abstract][Hide abstract] ABSTRACT: Motivated by the possibility of decreasing the intersymbol interference (ISI) which is due to large delays of a multipath mobile radio channel, orthogonal frequency division multiplexing (OFDM) became very popular. However, the timevariance of the mobile radio channel induces intercarrier
interference (ICI) yielding substantial channel estimation errors
and thereby tremendous transmission impairments. Contrary
to previous algorithms which resort to a linearization of the
time-variant channel, we combat the ICI using eigenspaces of
time-domain covariance matrices defined by the autocorrelation
function of the Doppler spread. We perform a basis expansion
using Slepian sequences and determine the basis coefficients of
the time-variant channel by channel estimates from previous
OFDM symbols. Once we know these basis coefficients, we
obtain the necessary time-variant channel estimation by the
Slepian sequences. These time-variant channel estimates allow
a symbol detection in frequency domain which eliminates the
ICI almost completely. Simulation results investigate both the
signal to interference ratio (SIR) and the bit error ratio (BER)
of our new ICI mitigation methods and reveal the superiority
compared to previous algorithms for ICI reduction.
[Show abstract][Hide abstract] ABSTRACT: Time Based (TB) localization in terrestrial mobile radio as an augmentation for global navigation satellite systems has recently gained plenty of interests. As an essential tool to develop suitable algorithms for positioning applications in mobile radios, channel models for wireless transmissions have growing significance. Currently there is a lack of investigations on comparing the propagation characteristics at 2.45 GHz and 5.2 GHz for positioning applications. Therefore, we present a statistic evaluation based on a channel measurement campaign. Several propagation characteristics are researched like the received power and the delay spread. While some measures like the received power is carrier frequency dependent, most of the measures like the non line-of-sight bias or the delay spread are independent of this measurement parameter. Instead they are more influenced by the location and the environment.
[Show abstract][Hide abstract] ABSTRACT: This paper presents a novel maximum likelihood (ML) time difference of arrival (TDoA) estimation algorithm for subsample delays. We introduce a new initial acquisition and cell search algorithm with implicit multiple access interference (MAI) cancelation. A joint carrier frequency offset (CFO) estimation and subsample delay estimation is used to compensate Doppler spreads and oscillator drifts. Analytical derivations show how the CFO influences the TDoA subsample delay estimation and vice versa. Furthermore, we show through numerical simulations that the geographic base station mapping and the used synchronization codes influence the estimation accuracy. Additionally, we introduce a new successive interference cancelation (SIC) to improve the overall accuracy.
[Show abstract][Hide abstract] ABSTRACT: This paper presents a novel analytical derivation of the false alarm probability (FAP) and detection probability (DP) for non-line-of-sight (NLOS) detection based on LTE signals. Position estimation in indoor or urban area with cellular wireless communication systems is getting more and more important. However, especially in these environments NLOS propagation causes positioning errors in the order of hundreds of meters. Thus, detection and mitigation of NLOS signals is a critical task. In this paper, we derive the FAP and DP on power-scaled detectors based on LTE multipath signals. The derivation considers frequency-selective fading channels taking sub-sample multipath interference, channel dynamics and initial frequency offsets into account. The results show a simple way to calculate the DP versus FAP. Simulation results verify the analytical probabilities for the WINNER II C2 channel model. Additionally, the simulations show the improved FAP of an antenna array at the receiver.
[Show abstract][Hide abstract] ABSTRACT: This paper presents a novel analytical derivation of the false alarm probability (FAP) and detection probability (DP) for non-line-of-sight (NLOS) detection of GNSS signals. The NLOS propagation in for example urban environments causes positioning errors in the order of hundreds of meters in navigation systems. Thus, detection and mitigation of NLOS signals is a critical task for high accuracy navigation receivers. In this paper, we derive the FAP and DP on power–scaled detectors based on the multipath signals. The derivation considers frequency–selective fading channels taking sub–chip multipath interference, channel dynamics and initial frequency offsets into account. The results show a simple way to calculate the DP versus FAP. Simulation results verify the analytical probabilities and show the trade–off between temporal non–coherent versus coherent averaging. Clearly, the optimum noise averaging depends on the length of the symbol sequence and channel dynamics. Additionally, the simulations show the improved DP of an antenna array at the receiver. Furthermore we see the influence of sub–chip interference in the simulation results.
[Show abstract][Hide abstract] ABSTRACT: This paper presents a novel non-line-of-sight (NLOS) detection algorithm for GNSS signals. It adapts the confidence metric, which was derived for ultra wide-band scenarios and is based on multipath propagation effects, to GNSS. The confidence metric indicates NLOS scenarios by comparing the signal power of the multipath components to the propagation time. Instead of considering the whole propagation time, we consider only the additionally propagation time of the multipath signals. This adapted algorithm is more stable against varying signal to noise ratio and outputs the probability whether the received signal is LOS or NLOS. Because the metric is based on the received GNSS multipath signal, a multipath mitigation algorithm is necessary to use the NLOS detection algorithm. Hence, this paper derives additionally the Cramer-Rao lower bound (CRLB) for a channel estimator with the estimation errors in the amplitudes and delays. Simulation results show the benefit using this metric in the position estimation by an extended Kalman filter. Additionally, we consider different scenarios with GPS only, GPS + Galileo and GPS + Galileo + LTE. Especially, if less than 4 LOS satellites are available, the LTE signals can improve the position estimation significantly.