Juan A. Fernández-Rubio

ML estimator and hybrid beamformer for multipath and interference mitigation in GNSS receivers

This paper addresses the estimation of the code-phase (pseudorange) and the carrier-phase of the direct signal received from a direct-sequence spread-spectrum satellite transmitter. The signal is received by an antenna array in a scenario with interference and multipath propagation. These two effects are generally the limiting error sources in most high-precision positioning applications. A new estimator of the code- and carrier-phases is derived by using a simplified signal model and the maximum likelihood (ML) principle. The simplified model consists essentially of gathering all signals, except for the direct one, in a component with unknown spatial correlation. The estimator exploits the knowledge of the direction-of-arrival of the direct signal and is much simpler than other estimators derived under more detailed signal models. Moreover, we present an iterative algorithm, that is adequate for a practical implementation and explores an interesting link between the ML estimator and a hybrid beamformer. The mean squared error and bias of the new estimator are computed for a number of scenarios and compared with those of other methods. The presented estimator and the hybrid beamforming outperform the existing techniques of comparable complexity and attains, in many situations, the Crame/spl acute/r-Rao lower bound of the problem at hand.

A Bayesian Approach to Multipath Mitigation in GNSS Receivers

Multipath is known to be one of the most dominant sources of accuracy degradation in satellite-based navigation systems. Multipath may cause biased position estimates that could jeopardize high-precision applications. This paper considers the problem of tracking the time-variant synchronization parameters of both the line-of-sight signal (LOSS) and its multipath replicas. In particular, the proposed algorithm tracks time-delays, amplitudes, phases and proposes a procedure to extract Doppler shifts from complex amplitudes. However, the interest is focused on LOSS time-delay estimates, since those provide the means to compute users position. The undertaken Bayesian approach is implemented by a particle filter. The selection of the importance density function, from which particles are generated, is performed using a Gaussian approximation of the posterior function. This selection provides a particle generating function close to the optimal, which yields to an efficient usage of particles. The complex-linear part of the model, i.e., complex amplitudes, is tackled by a Rao-Blackwellization procedure that implements a complex Kalman filter for each generated particle, thus reducing the computational load. Computer simulation results are compared to other Bayesian filtering alternatives (namely, the extended Kalman filter, the unscented Kalman filter and the sequential importance resampling algorithms) and the posterior Cramer-Rao bound.

CramÉr–Rao Bound Analysis of Positioning Approaches in GNSS Receivers

Recently, direct position estimation (DPE) has arisen as a potential approach to deal with the positioning problem in global navigation satellite system receivers. The conventional navigation solution is obtained in two steps: synchronization parameters are estimated and then a trilateration procedure is in charge of computing users position, based on those parameters. In contrast, DPE estimates receivers position directly from digitized signal. DPE was seen to provide GNSS receivers with appealing capabilities, such as multipath mitigation. However, a theoretical bound for those estimates is still missing and the answer to ldquohow better can DPE perform compared to the conventional approach?rdquo has not been addressed in the literature. Aiming at clarifying those issues, this paper presents the derivation of the CramEacuter-Rao bound (CRB) of position for both conventional and DPE approaches. We present the derivation for a multiantenna receiver as a general case. In addition, a number of realistic scenarios are tested in order to compare the theoretical performance bounds of both alternatives and the actual root mean squared error performance of the corresponding maximum likelihood estimator.

A game theoretical algorithm for joint power and topology control in distributed WSN

In this paper, the issue of network topology control in wireless networks using a fully distributed algorithm is considered. Whereas the proposed distributed algorithm is designed applying game theory concepts to design a non-cooperative game, network connectivity is guaranteed based on asymptotic results of network connectivity. Simulations show that for a relatively low node density, the probability that the proposed algorithm leads to a connected network is close to one.

Bayesian Dll for Multipath Mitigation in Navigation Systems Using Particle Filters

In direct-sequence spread-spectrum (DS-SS) navigation based systems, multipath can degrade seriously synchronization performance causing time delay and code phase estimates, to deviate from the actual value. This bias depends on the relative amplitudes and delays of multipath replicas with respect to the direct signal. The error in the estimated position due to multipath, when using a standard delay lock loop, can be on the order of several tens of meters, which is a critical aspect in high-precision applications. This works presents a sequential Monte Carlo based algorithm which tries to iteratively estimate complex amplitudes and delays of the direct signal and multipath replicas by characterizing the posterior probability density function of these parameters relying on particle filter theory. Simulations are presented for navigation systems, which are particular applications of DS-SS systems

Cancellation of external and multiple access interference in CDMA systems using antenna arrays

This paper deals with the problem of multisensor-multiuser detection in CDMA systems in the presence of interferences external to the system. The paper presents a new method able to estimate the spatial signature of all active users projected onto the subspace orthogonal to the external interference. With this information a specific beamformer can be designed for each user in order to combat the external and multiple access interference. The method performs in frequency non-selective multipath scenarios as they arise from some CDMA satellite and indoor communications systems. The estimation process does not require any training signal nor any a priori spatial information. It exploits the temporal structure of CDMA signals and extract the required information directly from the received signals. In addition, the method is independent of the nature of the external interference and it can cope with narrow-band and wide-band interfering signals.This paper deals with the problem of multisensor-multiuser detection in CDMA systems in the presence of interferences external to the system. The paper presents a new method able to estimate the spatial signature of all active users projected onto the subspace orthogonal to the external interference. With this information a specific beamformer can be designed for each user in order to combat the external and multiple access interference. The method performs in frequency non-selective multipath scenarios as they arise from some CDMA satellite and indoor communications systems. The estimation process does not require any training signal nor any a priori spatial information. It exploits the temporal structure of CDMA signals and extract the required information directly from the received signals. In addition, the method is independent of the nature of the external interference and it can cope with narrow-band and wide-band interfering signals.

ML Estimation of Position in a GNSS Receiver using the SAGE Algorithm

In this paper, the maximum likelihood estimator (MLE) of the position in satellite based navigation systems is studied. Recent results have shown that this novel approach provides an interesting way of introducing prior information in the position estimation and that the estimator is consistent for large sample sizes. However, one of the main drawbacks of this approach is the lack of a computationally efficient optimization algorithm due to the high dimensionality and nonlinearity of the resulting cost function, since there is not a closed form solution for this estimator. The aim of this paper is to investigate the application of the space-alternating generalized expectation maximization (SAGE) algorithm to the estimation of position. The SAGE algorithm is a low-complexity generalization of the EM (expectation-maximization) algorithm, which iteratively approximates the MLE. Computer simulation results are provided, comparing the performance obtained by the algorithm with the Cramer-Rao bound.

Coupling noise effect in self-synchronizing wireless sensor networks

Recent results have shown that the mathematical tools considered for modelling populations of coupled oscillators appearing in nature provide an appealing framework for designing self-syncronizing sensor networks. Trendy signal processing applications take advantage of these works by coupling the sensors in order to design reliable decision/estimation networks based on cheap and unreliable sensors. In this work, we extend those results to take into account that the coupling function might suffer from noise due to the need of estimating the states of the nearby sensors. The novelty of this paper is the introduction of the concept of frustration in the design of wireless sensor networks. Frustration implies that synchronization is only possible up to a certain variance standstill floor. We provide the analytic expression of this floor and discuss some limiting cases. In order to assess the performance of the self-synchronizing network, we propose a simple signal model for the transmission of states from node to node and study its Cramer-Rao Bound and the asymptotically efficient Maximum Likelihood estimator. Taking into consideration these achieved estimation variances, computer simulation results are provided discussing the coupling noise effect and the obtained theoretical lower bound.

Cramér-Rao lower bound for breakpoint distance estimation in a path-loss model

This paper addresses the problem of determining the Cramér-Rao lower bound (CRLB) for the parameters and breakpoint distance in a Path-Loss Channel model for Received Signal Strength (RSS) measurements. The path loss model is usually assumed for corrupted RSS measurements due to the shadow fading channel feature. In this paper the two-slope path loss model is considered, in which RSS measurements are modeled differently for close and far distances. Closed-form expressions for the CRLB parameters are derived for unknown breakpoint distance. For unknown parameters and breakpoint distance value, a Bayesian estimation method is proposed. The CRLB is then compared with the performance of the herein proposed method. The comparison illustrates convergence and efficiency of the Bayesian estimator.

Code-timing synchronization in DS-CDMA systems using space-time diversity

The synchronization of a desired user transmitting a known training sequence in a direct-sequence (DS) asynchronous code-division multiple-access (CDMA) system is addressed. It is assumed that the receiver consists of an arbitrary antenna arrayand works in a near–far, frequency -nonselective, slowlyfading channel. The estimator that we propose is derived byapply ing the maximum likelihood (ML) principle to a signal model in which the contribution of all the interfering components (e.g., multiple-access interference, external interference and noise) is modeled as a Gaussian term with an unknown and arbitraryspace–time correlation matrix. The main contribution of this paper is the fact that the estimator makes e7cient use of the structure of the signals in both the space and time domains. Its performance is compared with the Cram+ er–Rao Bound, and with the performance of other methods proposed recentlythat also employan antenna arraybut onlyexploit the structure of the signals in one of the two domains, while using the other simplyas a means of path diversity . It is shown that the use of the temporal and spatial structures is necessary to achieve synchronization in heavily loaded systems or in the presence of directional external interference. ? 2001 Elsevier Science B.V. All rights reserved.