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Livraison de contenu sur réseau hybride satellite-terrestre

Authors: Bouttier Elie, Dhaou Riadh, Arnal Fabrice, Baudoin Cédric, Dubois Emmanuel and Beylot André-Luc

Seminars of TéSA, Toulouse, April 19, 2016.

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Networking / Other

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Continuous Phase Modulation - A short Introduction

Authors: Piat-Durozoi Charles-Ugo and Chayot Romain

Seminars of TéSA, Toulouse, April 19, 2016.

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Digital communications / Aeronautical communication systems and Space communication systems

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Journal Paper

On Lower Bounds for Nonstandard Deterministic Estimation

Authors: Kbayer Nabil, Galy Jérôme, Chaumette Eric, Vincent François, Renaux Alexandre and Larzabal Pascal

IEEE Transactions on Signal Processing, vol. 65, n° 6, pp. 1538-1553, March, 2017.

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We consider deterministic parameter estimation and the situation where the probability density function (p.d.f.) parameterized by unknown deterministic parameters results from the marginalization of a joint p.d.f. depending on random variables as well. Unfortunately, in the general case, this marginalization is mathematically intractable, which prevents from using the known standard deterministic lower bounds (LBs) on the mean squared error (MSE). Actually the general case can be tackled by embedding the initial observation space in a hybrid one where any standard LB can be transformed into a modified one fitted to nonstandard deterministic estimation, at the expense of tightness however. Furthermore, these modified LBs (MLBs) appears to include the submatrix of hybrid LBs which is an LB for the deterministic parameters.Moreover, since in the nonstandard estimation, maximum likelihood estimators (MLEs) can be no longer derived, suboptimal nonstandard MLEs (NSMLEs) are proposed as being a substitute. We show that any standard LB on the MSE of MLEs has a nonstandard version lower bounding the MSE of NSMLEs. We provide an analysis of the relative performance of the NSMLEs, as well as a comparison with the MLBs for a large class of estimation problems. Last, the general approach introduced is exemplified, among other things, with a new look at the well-known Gaussian complex observation models.

Signal and image processing / Aeronautical communication systems, Earth observation, Localization and navigation and Space communication systems

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Conference Paper

Multisymbol with Memory Noncoherent Detection of CPFSK

Authors: Piat-Durozoi Charles-Ugo, Poulliat Charly, Boucheret Marie-Laure, Thomas Nathalie, Bouisson Emmanuel and Lesthievent Guy

In Proc. IEEE Int. Conf. Acoust., Speech and Signal Proces. (ICASSP), La Nouvelle-Orléans, Louisiane-USA, March 5-9, 2017.

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Multisymbol receiver is an effective method to demodulate noncoherent sequences. However it is necessary to correlate an important number of symbols in a noncoherent scheme to reach the performances carried out by optimal coherent Maximum a Posteriori (MAP) detectors such as BCJR. In this paper, we propose an advanced multisymbol receiver by adding some memory to the decision process. The advanced receiver, called here Multisymbol With Memory (MWM) takes into account the cumulative phase information unlike multisymbol algorithm and thus it can be seen as a truncated BCJR. An exact mathematical derivation is performed for this truncated BCJR. Then an implementation of the MWM detector applied to a continuous phase frequency shift keying modulation is presented. Finally an asymptotic analysis is carried out based on the achievable Symmetric Mutual Information rate. The proposed system exhibits good performances compared to classical multisymbol receivers at the expense of increased complexity and can approach the performances of a coherent receiver.

Digital communications / Space communication systems

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Joint Channel and Carrier Frequency Estimation for M-ARY CPM over Frequency-Selective Channel using PAM Decomposition

Authors: Chayot Romain, Boucheret Marie-Laure, Poulliat Charly, Thomas Nathalie, Van Wambeke Nicolas and Lesthievent Guy

In Proc. IEEE Int. Conf. Acoust., Speech and Signal Proces. (ICASSP), La Nouvelle-Orléans, Louisiane-USA, March 5-9, 2017.

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In this paper, we present a new data-aided carrier-recovery method for Continuous Phase Modulation (CPM) signals over frequency-selective channels. We first present a linear model of the received signal based on Mengali representation over selective channels and show how to use it to perform joint channel and carrier-frequency estimation. We also derive a low-complexity version of the estimator. Simulation results show that this method performs better than the optimal method suited to the Additive White Gaussian Noise (AWGN) channels.

Digital communications / Aeronautical communication systems and Space communication systems

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Estimation Accuracy of Non-Standard Maximum Likelihood Estimators

Authors: Kbayer Nabil, Galy Jérôme, Chaumette Eric, Vincent François, Renaux Alexandre and Larzabal Pascal

In Proc. IEEE Int. Conf. Acoust., Speech and Signal Proces. (ICASSP), La Nouvelle-Orléans, Louisiane-USA, March 5-9, 2017.

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In many deterministic estimation problems, the probability density function (p.d.f.) parameterized by unknown deterministic parameters results from the marginalization of a joint p.d.f. depending on additional random variables. Unfortunately, this marginalization is often mathematically intractable, which prevents from using standard maximum likelihood estimators (MLEs) or any standard lower bound on their mean squared error (MSE). To circumvent this problem, the use of joint MLEs of deterministic and random parameters are proposed as being a substitute. It is shown that, regarding the deterministic parameters : 1) the joint MLEs provide generally suboptimal estimates in any asymptotic regions of operation yielding unbiased efficient estimates, 2) any representative of the two general classes of lower bounds, respectively the Small-Error bounds and the Large-Error bounds, has a ”non-standard” version lower bounding the MSE of the deterministic parameters estimate.

Signal and image processing / Aeronautical communication systems, Earth observation, Localization and navigation and Space communication systems

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Evaluation of Communication Performance For Adaptive Optics Corrected Geo-To-Ground Laser Links

Authors: Canuet Lucien, Vedrenne Nicolas, Conan Jean-Marc, Artaud Géraldine, Rissons Angélique and Lacan Jérôme

In Proc. International Conference on Space Optics (ICSO 2016), Biarritz, France, October 18-21, 2017.

For future GEO to ground communications link, very high throughput might be achievable at a reasonable cost assuming the use of existing single mode components developed for fiber technologies (optical detectors and amplifiers, MUX/DEMUX...). The influence of atmospheric turbulence degrades the injection efficiency of the incoming wave into single mode components. This leads to signal fading and channel impairments. Several mitigation strategies are considered to prevent them. The use of adaptive optics should contribute to reduce substantially the criticality of the fading at the expense of potentially complex and expensive systems if very high stability of the injection is requested. The use of appropriate interleaving can help to relax the specifications and cost of AO systems but could lead to unmanageable buffer size. Thus the specification of AO correction and interleavers should be addressed jointly. An analytical model to evaluate the channel capacity in terms of outage probability and packet error rate has been developed that jointly takes into account partial correction by AO and channel interleaving. The influence of partial correction is inferred from statistical and temporal properties of the corrected wavefront that are explicitly related to injection efficiency. Among others an analytical evaluation of the mean fading time is provided. Interleaving is taken into account with a block fading model. This model is presented here and confronted to numerical simulations for two distinct correction cases. The accuracy of the model is discussed. The interdependence of AO correction with interleaving is investigated.

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Journal Paper

Multi-Band Image Fusion Based on Spectral Unmixing

Authors: Wei Qi, Bioucas Dias José Manuel, Dobigeon Nicolas and Tourneret Jean-Yves

IEEE Transactions on Geoscience and Remote Sensing, vol. 54, n° 12, pp. 7236-7249, December, 2016.

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This paper presents a multi-band image fusion algorithm based on unsupervised spectral unmixing for combining a high-spatial low-spectral resolution image and a low-spatial high-spectral resolution image. The widely used linear observation model (with additive Gaussian noise) is combined with the linear spectral mixture model to form the likelihoods of the observations. The non-negativity and sum-to-one constraints resulting from the intrinsic physical properties of the abundances are introduced as prior information to regularize this ill-posed problem. The joint fusion and unmixing problem is then formulated as maximizing the joint posterior distribution with respect to the endmember signatures and abundance maps, This optimization problem is attacked with an alternating optimization strategy. The two resulting sub-problems are convex and are solved efficiently using the alternating direction method of multipliers. Experiments are conducted for both synthetic and semi-real data. Simulation results show that the proposed unmixing based fusion scheme improves both the abundance and endmember estimation comparing with the state-of-the-art joint fusion and unmixing algorithms.

Signal and image processing / Earth observation

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A Bayesian Nonparametric Model Coupled with a Markov Random Field for Change Detection in Heterogeneous Remote Sensing Images

Authors: Prendes Jorge, Chabert Marie, Giros Alain, Pascal Frédéric and Tourneret Jean-Yves

SIAM Journal on Imaging Sciences (SIIMS), vol. 9, n° 4, pp. 1888-1921, December, 2016.

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In recent years, remote sensing of the Earth surface using images acquired from aircraft or satellites has gained a lot of attention. The acquisition technology has been evolving fast and, as a consequence, many different kinds of sensors (e.g., optical, radar, multispectral, and hyperspectral) are now available to capture different features of the observed scene. One of the main objectives of remote sensing is to monitor changes on the Earth surface. Change detection has been thoroughly studied in the case of images acquired by the same sensors (mainly optical or radar sensors). However, due to the diversity and complementarity of the images, change detection between images acquired with different kinds of sensors (sometimes referred to as heterogeneous sensors) is clearly an interesting problem. A statistical model and a change detection strategy were recently introduced in [J. Prendes, M. Chabert, F. Pascal, A. Giros, and J.-Y. Tourneret, Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, Florence, Italy, 2014; IEEE Trans. Image Process., 24 (2015), pp. 799–812] to deal with images captured by heterogeneous sensors. The main idea of the suggested strategy was to model the objects contained in an analysis window by mixtures of distributions. The manifold defined by these mixtures was then learned using training data belonging to unchanged areas. The changes were finally detected by thresholding an appropriate distance to the estimated manifold. This paper goes a step further by introducing a Bayesian nonparametric framework allowing us to deal with an unknown number of objects in analysis windows without specifying an upper bound for this number. A Markov random field is also introduced to account for the spatial correlation between neighboring pixels. The proposed change detector is validated using different sets of synthetic and real images (including pairs of optical images and pairs of optical and radar images) showing a significant improvement when compared to existing algorithms.

Signal and image processing / Earth observation

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Conference Paper

Estimation of Timing Offsets and Phase Shifts Between Packet Replicas in MARSALA Random Access

Authors: Zidane Karine, Lacan Jérôme, Gineste Mathieu, Bès Caroline, Deramecourt Arnaud and Dervin Mathieu

In Proc. Global Communications Conference (IEEE/GLOBECOM) Washington DC, USA, December 4-8, 2016.

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Multi-replicA decoding using corRelation baSed LocALisAtion (MARSALA) is a recent random access technique designed for satellite return links. It follows the multiple transmission and interference cancellation scheme of Contention Resolution Diversity Slotted Aloha (CRDSA). In addition, at the receiver side, MARSALA uses autocorrelation to localise replicas of a same packet so as to coherently combine them. Previous work has shown good performance of MARSALA with an assumption of ideal channel state information and perfectly coherent combining of the different replicas of a given packet. However, in a real system, synchronisation errors such as timing offsets and phase shifts between the replicas on separate timeslots will result in less constructive combining of the received signals. This paper describes a method to estimate and compensate the timing and phase differences between the replicas, prior to their combination. Then, the impact of signal misalignment in terms of residual timing offsets and phase shifts, is modeled and evaluated analytically. Finally, the performance of MARSALA in realistic channel conditions is assessed through simulations, and compared to CRDSA in various scenarios.

Digital communications / Space communication systems

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TeSA in New Orleans

Charles-Ugo Piat-Durozoi (left) and Romain Chayot (right) presented papers at ICASSP 2017 last March, supported by Corinne Mailhes (center).

PhD positions available at TeSA

PhD subjects available on the CNES site.
On line application before the 31rst of March.

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Welcome to our 3 new PhD students: Adrien, Lorenzo and Selma (from left to right).