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Kalman tracking for mobile location in NLOS situations

This paper deals with the problem of nonline-of-sight (NLOS) in wireless communications systems devoted to location purposes. It is well known that NLOS biases time of arrival (TOA) and time difference of arrival (TDOA) estimates thus reducing accuracy of positioning algorithms. In order to achieve positioning error reduction the Kalman filter proposed for location estimation includes the time measurement bias for each base station (BS) as additional parameters to be estimated. The use of the Kalman filter allows then tracking, not only the position and speed of the mobile, but also the bias due to NLOS, yielding an accurate location prediction algorithm.

Mobile location with bias tracking in non-line-of-sight

The main impairment for the location of terminals in a wireless communications system is the non-line-of-sight (NLOS) condition which is mainly due to blocking of the transmitted signal by obstacles. It is well known that NLOS biases time-of-arrival (TOA) and time-difference-of-arrival (TDOA) estimates, therefore providing a biased position. The paper analyzes the improvements in positioning accuracy by tracking the bias of the time measures with the Kalman filter proposed for location estimation. The evaluation of the approach has been carried out with measures taken in real scenarios, for positioning techniques based on TDOA and TOA+AOA (angle of arrival) measurements.

High resolution time-of-arrival detection for wireless positioning systems

It is well known that non-line-of-sight (NLOS) and multipath propagation biases time of arrival (TOA) and time difference of arrival (TDOA) estimates, thus reducing accuracy of positioning algorithms. In order to achieve timing error reduction, a high-resolution first arriving path detector from propagation channel estimates is derived based on the minimum variance (MV) estimates and normalized minimum variance (NMV) of the power delay profile. The objective of the paper is to determine the potentialities of this optimal detection scheme within the framework of a realistic wireless positioning system. To this end, the timing measurements obtained are fed to a Kalman tracker which finally determines the position with a high degree of accuracy.

Performance comparison between FBMC and OFDM in MIMO systems under channel uncertainty

In this paper we present a performance comparison between two different multi-carrier transmission techniques: OFDM, based on the FFT and cyclic prefix (CP) addition; and FBMC (FilterBank MultiCarrier), which, as indicated by its name, is based on a filterbank architecture. For both schemes, we propose a joint beamforming design to be applied in multi-input-multi-output (MIMO) systems, which requires channel state information (CSI) at both communication ends. If perfect CSI is assumed, FBMC presents a higher energy-efficiency since it does not require a CP, differently to OFDM. However, in the imperfect CSI case, the opposite occurs: while in OFDM the presence of errors in the CSI does not cause intersymbol interference (ISI) and inter-carrier interference (ICI), in the FBMC case we show, both analytically and through simulation results, that imperfections in the CSI imply both ISI and ICI, which leads to an energy-efficiency loss. To mitigate this loss, we propose a novel robust receive beamforming strategy. In the simulations section, the performance of FBMC with robust beamforming is shown to outperform OFDM even in imperfect CSI conditions. The characterization of the tradeoff between energy-efficiency and robustness against channel uncertainty, both with robust and non-robust strategies, is, therefore, the objective of the present paper and also the motivation for future robust designs for FBMC multiantenna systems.

Kalman tracking based on TDOA for UMTS mobile location

A potentiality of the location problem in wireless networks that has not been explored enough is the mobility of the user equipment (UE). This paper deals with UMTS mobile location tracking using Kalman filtering based on TDOA (time difference of arrival) measurements. The performance of the proposed approach is compared with the CRB (Cramer Rao bound) for the static location estimator.

Energy efficient communications over the AWGN relay channel

This paper addresses the energy efficiency analysis of the relay channel under additive white Gaussian noise. We consider the rate bounds given by decode and forward and the cut set bound and assume that resources are optimally allocated to maximize the spectral efficiency according to the channel information and the sum network energy. The low energy analysis tools are used to compute the maximum rate per energy (RPE) and the slope of the spectral efficiency as a function of the energy per bit. Using these metrics, the energy efficiency benefit of several capabilities at terminals is investigated. Specifically, we take into account: (i) the phase synchronization between transmitters, (ii) the full duplex capability at the relay and (iii) the channel access via superposition.

Frequency Domain Joint TOA and DOA Estimation in IR-UWB

This paper addresses the problem of TOA and DOA estimation in IR-UWB systems. It considers a frequency domain approach for joint high resolution estimation of Time Of Arrival (TOA) and Direction Of Arrival (DOA). The proposed scheme performs timing acquisition following a two step approach: a first stage where coarse symbol timing is achieved by means of chip energy estimation and a minimum distance criterion based on the time-hopping sequence knowledge, followed by a reduced complexity high resolution TOA estimator that provides fine timing acquisition. The proposed algorithm can resolve time synchronization blindly, without the need for channel estimation and can operate on a single symbol basis. DOA estimation is then obtained from TOA estimates at each array element applying a linear estimator. The joint estimation of TOA and DOA provides robustness and potentially allows positioning with a single reference node. Furthermore, the paper derives the Cramer-Rao Lower Bound from a frequency domain signal model for a multipath channel where no assumptions are made with respect to the paths, which results in a compact closed form.

Blind wideband source separation

This paper deals with the general problem of separating two independent wideband sources when they are mixed by unknown filters. In order to solve this problem, a backward framework is proposed which is composed of two different stages. The first one consists of two linear predictors devoted to improve the source separation, whitening the input signals. Their coefficients are calculated applying the LMS algorithm, minimizing the mean squared errors between the predicted signals and the output of the separation network. The second stage is formed by decoupling filters that have to be blindly estimated imposing an independence criterion to the outputs.<<ETX>>

TOA and DOA Estimation for Positioning and Tracking in IR-UWB

This paper deals with positioning in impulse radio UWB (IR-UWB) based on time-of-arrival (TOA) and direction-of-arrival (DOA). We consider array processing at the receiver which allows low complexity joint estimation of TOA and DOA in frequency domain, previously proposed by the authors. The use of array processing provides robustness and potentially allows positioning with a single reference node. A position tracking algorithm based on the extended Kalman filter (EKF) from TOA and DOA measurements is proposed and evaluated.

Determining building interior structures using compressive sensing

Abstract. We consider imaging of the building interior structures using compressive sensing (CS) with applications to through-the-wall imaging and urban sensing. We consider a monostatic synthetic aperture radar imaging system employing stepped frequency waveform. The proposed approach exploits prior information of building construction practices to form an appropriate sparse representation of the building interior layout. We devise a dictionary of possible wall locations, which is consistent with the fact that interior walls are typically parallel or perpendicular to the front wall. The dictionary accounts for the dominant normal angle reflections from exterior and interior walls for the monostatic imaging system. CS is applied to a reduced set of observations to recover the true positions of the walls. Additional information about interior walls can be obtained using a dictionary of possible corner reflectors, which is the response of the junction of two walls. Supporting results based on simulation and laboratory experiments are provided. It is shown that the proposed sparsifying basis outperforms the conventional through-the-wall CS model, the wavelet sparsifying basis, and the block sparse model for building interior layout detection.