In this paper, we consider a bit-interleaved coded modulation scheme (BICM) composed of an error correcting code serially concatenated with a M-ary non linear modulation with memory. We first compare demodulation strategies for both the coherent and the non coherent cases. Then, we perform an asymptotic analysis and try to show that the design of coding schemes performing well for both the coherent and the non coherent regimes should be done carefully when considering sparse graph based codes such as low-density parity-check (LDPC) codes. It will be shown that optimized coding schemes for the non coherent setting can perform fairly well when using coherent demodulation, while on the contrary, optimized coding schemes for the coherent setting may lead to ”non stable” coding schemes in the non coherent setting.

This paper studies a maritime vessel detection method based on the fusion of data obtained from two different sensors, namely a synthetic aperture radar (SAR) and an automatic identification system (AIS) embedded in a satellite. In this work we propose a detector that uses the vessel position provided by the AIS system to improve the radar detection performance. The problem is handled by a generalized likelihood ratio test leading to a detector whose test statistics has a simple closed form expression. The distribution of the test statistics under the hypotheses is also determined, allowing theoretical and simulated receiver operational characteristics (ROCs) to be compared. Our results indicate that the proposed method improves detection performance and motivates the joint use of raw radar data with AIS demodulated information for ship detection.

Deriving a meaningful functional brain parcellation is a very challenging issue in task-related fMRI analysis. The joint parcellation detection estimation model addresses this issue by inferring the parcels from fMRI data. However, it requires a priori fixing the number of parcels through an initial mask for parcellation. Hence, this difficult task generally depends on the subject. The proposed automatic parcellation approach in this paper overcomes this limitation at the subject-level relying on a Dirichlet process mixture model combined with a hidden Markov random field to estimate the parcels and their number online. The proposed method adopts a variational expectation maximization strategy for inference. Compared to the model selection procedure in the joint parcellation detection estimation framework, our method appears more efficient in terms of computational time and does not require finely tuned initialization. Synthetic data experiments show that our method is able to estimate the right model order and an accurate parcellation. Real data results demonstrate the ability of our method to aggregate parcels with similar hemodynamic behaviour in the right motor and bilateral occipital cortices while its discriminating power is increased compared to its ancestors. Moreover, the obtained HRF estimates are close to the canonical HRF in both cortices.

This paper addresses the problem of estimating the roll-off factor of a received communication signal. We study two new statistical estimation methods that determine the roll-off factor by minimizing the difference between the theoretical and empirical power or power spectral density of the received signal. Another interesting contribution is the derivation of the roll-off Cramér–Rao bound which provides a reference in terms of estimation variance. Simulation results conducted on synthetic data allow the performance of the proposed methods to be evaluated. They are compared to a recent technique based on the amplitude fluctuations of the power spectral density associated with the received communication signal. The estimation methods are shown to be robust to channel impairments (including white Gaussian noise and synchronization errors). The proposed strategies are finally tested on real signals with known ground truth showing their possible application to digital communication problems.

L'augmentation continue de la demande en bande passante pousse les opérateurs à déployer toujours plus d'antennes, et les force à une réutilisation plus agressive des ressources spectrales. Allouer ces ressources aux utilisateurs devient alors une opération délicate, où les interférences jouent un rôle central. Sur le lien montant, le problème est d'autant plus difficile que le niveau d'interférence est fortement lié aux utilisateurs à qui les ressources sont allouées. Cet article traite de l'affectation des ressources (spectrales et temporelles) pour les satellites multi-faisceaux. Cette thématique a été largement étudiée dans le contexte des réseaux cellulaires terrestres, le contexte satellitaire s'en distingue notamment par sa méthode d'accès, ce qui implique des modifications dans le modèle et dans sa méthode de résolution. Une modélisation spécifique du problème est alors présentée, sous la forme d'un problème d'optimisation linéaire en nombres entiers, cherchant à maximiser l'efficacité spectrale du système. Puis l'impact de simplifications exploitant la structure du problème est étudié, permettant de calculer une borne supérieure pour des scénarios réalistes.

High throughput satellites have proven to be an excellent solution to provide Internet services to white spots or to complement other existing infrastructures. With the use of multi-beam antennas, the same frequency may be reused dozens of times across a single satellite coverage area, increasing the system capacity and profitability. Legacy frequency reuse patterns such as uncoordinated 4-color scheme ensure interference isolation at the expense of important capacity reduction, using only one fourth of the operator's share in the scarce Ka band. Thus, to increase the per-beam available bandwidth, it is necessary to look for more aggressive and efficient Frequency Reuse schemes, generating higher Co-Channel Interference which has to be analyzed and handled. In this paper, we focus on the DVB-RCS2 return link of a multi-beam satellite and investigate the possibility of reaching the upper bound of a coordinated 2-color system capacity through the use of Interference-aware User Scheduling techniques. We first formalize the problem as an Integer Linear Program and study the impact of greedy simplifications on the optimality and processing times of our optimization models.

Considered as the free accessible and suitable solution for positioning in urban areas, Global Navigation Satellite Systems (GNSS) have been widely used these recent years in a wide spectrum of applications. However, signal blockage, non-line-of-sight (NLOS) multipath interferences and signal degradation affect the system performance and represent the major hurdles of GNSS in it course of adoption as a main localization technology in urban environments. Many approaches have been employed to constructively use these degraded signals in order to reduce positioning errors. Following this vision, we propose in this paper a joint estimation method of the position and the bias for measurement correction. This formulation leads to an ill-conditioned estimation problem. In this work, we apply a regularized robust estimation framework to this problem of NLOS mitigation for GNSS positioning in harsh areas. We derive the optimal regularization matrix by minimizing the total Mean Square Errors (MSE) of the considered model. The performance of the proposed method is assessed using real GNSS data collected in a dense urban area in Toulouse City, showing improvements in comparison to some existing methods.

Le procédé de positionnement comprend l'estimation d'un ensemble de biais multitrajets sur la base d'un modèle théorique des écarts entre les pseudo-distances mesurées et les pseudo-distances estimées. Le modèle comprend un terme de géométrie dépendant de la position du récepteur GNSS et des émetteurs GNSS et un terme additif représentant l'ensemble desdits biais. Les inconnues du modèle comprennent la position courante du récepteur GNSS et lesdits biais. L'estimation des biais repose sur une minimisation des résidus entre les écarts et le modèle théorique, en fonction des inconnues, sous la contrainte que l'ensemble des biais doit être parcimonieux. Les pseudo-distances mesurées sont corrigées sur base des biais estimés et une position courante du récepteur GNSS est prédite sur la base des pseudo-distances mesurées ainsi corrigées. L'invention permet de réduire l'impact des multi-trajets sur la solution de positionnement et donc d'en améliorer l'exactitude.

This study deals with the sense and avoid problem for an helicopter. The objective of such a system is to early detect collision targets (typically high-voltage wires). The direction of arrival (DoA) of the target is then a crucial information. In severe multipath environments (flight over a river, for instance), classical DoA estimation schemes dramatically degrade. The authors make use of a method based on the maximum likelihood (ML) principle that can resolve two highly correlated and close targets. The major drawback of ML algorithms, namely the computational burden, is removed using an approximation for closely space targets. The contribution of this study is twofold. The authors first extend the approximated ML DoA estimation to the case of non-uniform linear antennas and complete the procedure by a detection scheme. Second, they attest the validity of this new processing on real radar data. Hence, they show that the proposed procedure is able to detect a high-voltage wire, over a river, at ranges up to 1 km, where a capon beamformer cannot.

A reliable leadfield matrix is needed to solve the magnetoencephalography/electroencephalography (M/EEG) source localization problem. The computation of this matrix requires several physical parameters, including the conductivity of the tissues that compose the subject's head. Since it is not precisely known, we modify a recent Bayesian algorithm to estimate the skull conductivity jointly with the brain activity directly from the M/EEG measurements. Synthetic and real data are used to compare our technique with two optimization algorithms, showing that the proposed method is able to provide results of similar or better quality with the advantage of being applicable in a more general case.