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Conference Paper

Processed 5G Signals Mathematical Models for Positioning considering a Non-Constant Propagation Channel

Authors: Tobie Anne-Marie, Garcia Pena Axel, Thevenon Paul and Aubault Marion

In Proc. Vehicular Technology Conference (VTC-Fall), Honolulu, Hawaii, USA, September 22-25, 2019.

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The objective of this paper is to determine the ranging performance of the upcoming fifth generation (5G) signal. In order to do so, it is required to define 5G correlator outputs mathematical models. 5G systems will use OFDM (Orthogonal Frequency Division Multiplexing) signals; in the literature, mathematical models of OFDM signals are developed at the different receiver signal processing stages. These models assumed that the propagation channel is constant over an OFDM symbol; nevertheless, an in-depth study of QuaDRiGa, a 5G compliant propagation channel simulator, invalidates this hypothesis. Therefore, in this paper, mathematical models are developed that take into account the channel evolution. The focus is given on correlator outputs and results are applied to the computation of 5G based pseudo range accuracy.

Digital communications / Localization and navigation

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Talk

Learning hidden Markov models for anomaly detection in time series

Authors: Leon Lopez Kareth, Arguello Fuentes Henry, Tourneret Jean-Yves and Mouret Florian

Seminar of TeSA, Toulouse, March 4, 2020.

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Hidden Markov models (HMM) have been widely used for sequence modeling, such as speech and proteins, where the sequential signal is modeled as a doubly stochastic process compound of a hidden sequence inferred from the observed one. HMM captures the temporal context of sequences through the model parameters. This work studies the anomaly detection problem in time series via the learning of HMM parameters from observable sequences. For this, the maximum likelihood estimation of normal sequences is used to learn the model that best characterizes the normal behavior of the observed signals. Then, the log-probability of test sequences is computed using the learned-HMM, where higher values indicate a high probability of being a normal sequence. As a case of study, the approach is applied to multitemporal remote sensing by using extracted indicators from 13 Sentinel-2 images of rapeseed crops. The detection performance is evaluated in terms of precision and recall, where the HMM-learning approach obtains comparable detection rates against classical anomaly detection methods.

Signal and image processing / Earth observation

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On the impact of intrinsic delay variation sources on Iridium LEO constellation

Authors: Boubaker Amal, Chaput Emmanuel, Beylot André-Luc, Kuhn Nicolas, Dupé Jean-Baptiste, Sallantin Renaud and Baudoin Cédric

Seminar of TeSA, Toulouse, March 4, 2020.

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The recent decades have seen an increasing interest in Medium Earth Orbit and Low Earth Orbit satellite constellations. However, there is little information on the delay variation characteristics of these systems and the resulting impact on high layer protocols. To fill this gap, this paper simulates a constellation that exhibits the same delay characteristics as the already deployed Iridium but considers closer bandwidths to constellation projects. We identify five major sources of delay variation in polar satellite constellations with different occurrence rates: elevation, intra-orbital handover, inter-orbital handover, orbital seam handover and Inter-Satellite Link changes. We simulate file transfers of different sizes to assess the impact of each of these delay variations on the file transfer. We conclude that the orbital seam is the less frequent source of delay and induces a larger impact on a small file transfers: the orbital seam, which occurs at most three times during 24 hours, induces a 66% increase of the time needed to transmit a small file. Inter-orbital and intra-orbital handovers occur less often and reduce the throughput by approximately ~ 8% for both low and high throughput configurations. The other sources of delay variations have a negligible impact on small file transfers, and long file transfers are not impacted much by the delay variations.

Networking / Space communication systems

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Journal Paper

Scheduling flows over LEO constellations on LMS channels

Authors: Tauran Bastien, Lochin Emmanuel, Lacan Jérôme, Arnal Fabrice, Gineste Mathieu and Kuhn Nicolas

International Journal of Satellite Communications and Networking ISSN 1542-0981, online, February, 2020.

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Satellite systems typically use physical and link layer reliability schemes to compensate the significant channel impairments, especially for the link between a satellite and a mobile end-user. These schemes have been introduced at the price of an increase in the end-to-end delay, high jitter or out-of-order packets. This is show to have a negative impact both on multimedia and best-effort traffic, decreasing the Quality of Experience (QoE) of users. In this paper, we propose to solve this issue by scheduling data transmission as a function of the channel condition. We first investigate existing scheduling mechanisms and analyze their performance for two kinds of traffic : VoIP and best-effort. In the case of VoIP traffic, the objective is to lower both latency and jitter, which are the most important metrics to achieve a consistent VoIP service. We select the best candidate among several schedulers and propose a novel algorithm speciffically designed to carry VoIP over LEO constellations. We then investigate the performance of the scheduling policies on Internet-browsing trac carried by TCP, where the goal is now the maximize the users' goodput, and select the best candidate in this case.

Networking / Space communication systems

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Bayesian 3D Reconstruction of Subsampled Multispectral Single-photon Lidar Signals

Authors: Tachella Julian, Altmann Yoann, Marquez Miguel, Arguello Fuentes Henry, Tourneret Jean-Yves and McLaughlin Stephen

IEEE Transactions on Computational Imaging, vol. 6, pp.208-220, 2020.

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Light detection and ranging (Lidar) single-photon devices capture range and intensity information from a 3D scene. This modality enables long range 3D reconstruction with high range precision and low laser power. A multispectral single-photon Lidar system provides additional spectral diversity, allowing the discrimination of different materials. However, the main drawback of such systems can be the long acquisition time needed to collect enough photons in each spectral band. In this work, we tackle this problem in two ways: first, we propose a Bayesian 3D reconstruction algorithm that is able to find multiple surfaces per pixel, using few photons, i.e., shorter acquisitions. In contrast to previous algorithms, the novel method processes jointly all the spectral bands, obtaining better reconstructions using less photon detections. The proposed model promotes spatial correlation between neighbouring points within a given surface using spatial point processes. Secondly, we account for different spatial and spectral subsampling schemes, which reduce the total number of measurements, without significant degradation of the reconstruction performance. In this way, the total acquisition time, memory requirements and computational time can be significantly reduced. The experiments performed using both synthetic and real single-photon Lidar data demonstrate the advantages of tailored sampling schemes over random alternatives. Furthermore, the proposed algorithm yields better estimates than other existing methods for multi-surface reconstruction using multispectral Lidar data.

Signal and image processing / Earth observation

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Conference Paper

One-step Generalized Likelihood Ratio Test for Subpixel Target Detection in Hyperspectral Imaging

Authors: Vincent François and Besson Olivier

In Proc. Computational Advances in Multi-Sensor Adaptive Processing (IEEE CAMSAP), Le Gosier, Guadeloupe, France, December 15-18, 2019.

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One of the main objectives of hyperspectral image processing is to detect a given target among an unknown background. The standard data to conduct such a detection is a reflectance map, where the spectral signatures of each pixel’s components, known as endmembers, are associated with their abundances in the pixel. Due to the low spatial resolution of most hyperspectral sensors, such a target occupies a fraction of the pixel. A widely used model in case of subpixel targets is the replacement model. Among the vast number of possible detectors, algorithms matched to the replacement model are quite rare. One of the few examples is the Finite Target Matched Filter, which is an adjustment of the well-known Matched Filter. In this paper, we derive the exact Generalized Likelihood Ratio Test for this model. This new detector can be used both with a local covariance estimation window or a global one. It is shown to outperform the standard target detectors on real data, especially for small covariance estimation windows.

Signal and image processing / Earth observation

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Subpixel Target Detection in Hyperspectral Imaging

Authors: Vincent François and Besson Olivier

In Proc. Computational Advances in Multi-Sensor Adaptive Processing (IEEE CAMSAP), Le Gosier, Guadeloupe, France, December 15-18, 2019.

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Detecting a target of known spectral signature from an unknown background is one of main goal of hyperspectral imaging. As the majority of hyperspectral imaging systems have a poor spatial resolution, subpixel targets are usual. In this case, the so-called replacement model is commonly advocated. This model, valid for reflectance images, specifies that if a target is present, the amount of background should reduce in the same proportion. Nevertheless, the majority of the standard detectors, such as the Match Filter or the Kelly detector, have been developed for different contexts, and do not exploit this constraint. One of the rare example that is suitable for the replacement model is the Finite Target Match Filter, which is known to improve the target selectivity detection. In this paper, we develop the exact Generalized Likelihood Ratio Test for the model at hand. We show that this new detector outperforms the standard ones, on a real data experiment.

Signal and image processing / Earth observation

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An analysis of NDN Congestion Control challenges

Authors: Thibaud Adrien, Fasson Julien, Arnal Fabrice, Sallantin Renaud, Dubois Emmanuel and Chaput Emmanuel

In Proc. Hot Information-Centric Networking (HotICN), Chongqing, China, December 13-15, 2019.

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Named Data Networking (NDN) proposes to change the core of the Internet. Based on mechanisms successfully used in P2P or CDN, it focuses on content and thus the Quality of Experience of users. Such an ambitious plan raises great challenges : caching, multipath, multi-producers, multi-consumers and security. This paper focuses on one of them: the control of congestion. Several studies have proposed congestion control solutions that fall into three kinds: the end-to-end solution, the hop-by-hop type and the hybrid one. However, the community lacks proper evaluations of such specific algorithms. In this work, we have implemented representative solutions on ndnSIM. In a first step, we have tested them on a small scale topology to ease their performance analysis and highlight their strengths and weaknesses. We complete this study with simulations on larger networks in order to confirm our conclusions. Furthermore, all results are reproducible. Eventually, the paper drives a discussion on how application needs could be considered in the design of a NDN congestion control.

Networking / Space communication systems

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PhD Thesis

Méthodes d'accès aléatoire pour les communications par satellite

Author: Zamoum Selma

Defended on November 28, 2019.

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The effective coverage of satellites and the technology behind have motivated many actors to develop efficient communications for Internet access, television and telephony. For a long time, reservation resources of Demand Assignment Multiple Access (DAMA) techniques have been largely deployed in the return link of satellite communications, occupying most of the frequency bandwidth. However, these resources cannot follow the technological growth with big users communities in applications like the Internet of Things and Machine to Machine communications. Especially because the Round Trip Time is significant in addition to a potential underuse of the resources. Thus, access protocols based on ALOHA took over a big part of the Random Access (RA) research area and have considerably evolved lately. CRDSA have particularly put its fingerprint in this domain, which inspired many different techniques. In this context, a complementary method, called MARSALA comes to unlock CRDSA when packets can no longer be retrieved. This actually involves a correlation complexity related to packet localization which is necessary for replicas combinations that results in a potentially higher signal power. Accordingly, the main goal of this PhD research is to seek for effective and less complex alternatives. More precisely, the core challenge focuses on the way to manage multi-user transmissions and solve interference at reception, with the smallest complexity. In addition, the loop phenomenon which occur when multiple users transmit their packets at the same positions is tackled as it creates an error floor at the packet loss ratio performance. Synchronous and asynchronous solutions are proposed in this thesis, mainly based on providing the transmitter and the receiver with a shared prior information that could help reduce the complexity, mitigate the loop phenomenon and enhance the system performance. An in-depth description and analysis of the proposed techniques are presented in this dissertation.

Digital communications / Space communication systems

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PhD Defense Slides

Random Access Techniques for Satellite Communications

Author: Zamoum Selma

Defended on November 28, 2019.

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Digital communications / Space communication systems

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Send your interest!

TeSA PhD co-funded by CNES and ONERA on image processing for archeology.

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Activity Report

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Pau Closas, Northeastern Univ Boston, in TeSA

TeSA welcomes him with a research fellowship for July!