Year: 2021

PhD Defence: “Gestion d’Interference Topologique pour les Réseaux Sans Fils Multi-utilisateurs”, Hassan Kallam, Amphitheater, Chappe Building, 28th of September 2021 at 14:00 PM

The defense will be held in the Amphitheater, Chappe Building.

 

Title

Gestion d’Interference Topologique pour les Réseaux Sans Fils Multi-utilisateurs

 

 

Abstract

La gestion d’interference topologique (de l’Anglais: Topological Interference Management – TIM) permet l’etude des dégrées de liberté (de l’Anglais: Degrees of Freedom – DoF) de réseaux sans fils soumis à l’interference partielle et dont la connaissance de l’état du canal est limitée seulement à la topologie du réseaux, autrement dit, les liens interférents faibles et forts. Dans ce manuscrit de thèse, nous considérons l’application de TIM pour les réseaux cellulaires d’une dimension (1D) linéaires et les réseaux cellulaires de deux dimensions (2D) hexagonales. Nous considérons le cas des utilisateurs uniformément distribués dans chaque cellule, ce qui donne une distribution continue d’utilisateurs. Ceci nous permet d’étudier la performance des classes d’utilisateurs au contraire des positions des utilisateurs individuels, comme a été fait auparavant. Nous considérons aussi la construction de la topologie au travers de l’analyse des seuils de l’interférence. Contrairement aux travaux existents nous utilisons TIM au niveau des classes des utilisateurs, ce qui nous permet de trouver la performance système en DoF indépendante de la position précise de chaque utilisateur. Ensuite, après avoir proposé un schéma de coloration fractionnaire des graphes resultants, pouvant atteindre la solution optimale de DoF, un compromis entre DoF et SIR est proposé. Cette thèse propose également une nouvelle approche pour construire une topologie d’interférence pour le problème TIM unicast des réseaux sans fil multi-utilisateurs. Fondée sur notre approche de construction de topologie d’interférence, nous pouvons évaluer la limite théorique des taux atteignables, dans le régime SNR asymptotique, pour le réseau sans fil sous-jacent et pas seulement pour sa représentation topologique d’interférence. Cette nouvelle approche nous permet de traiter le régime de SNR fini et pas seulement le régime SNR asymptotique avec l’analyse DoF. Un nouveau paramètre liée au seuil d’interférence, indépendant du SNR, est proposé et nous évaluons les débits symétriques réalisables du réseau sans fil, à la fois en régime SNR fini et en régime SNR asymptotique. Ensuite, nous présentons les bornes supérieures sur ce nouveau paramètre de seuil d’interférence normalisé pour les topologies d’interférence ayant une faisabilité en demi-DoF (de l’Anglais: Half-DoF-feasible), en considérant à la fois une allocation de ressources orthogonale et l’alignement d’interference (de l’Anglais: Interference Alignment – IA). Ces limites spécifient si une topologie d’interférence donnée realisable en demi-DoF peut être, en termes de taux réalisable, la meilleure topologie ou non. En utilisant ce résultat, nous limitons l’espace de recherche dans la plage de paramètres du seuil d’interférence normalisée, pour trouver des topologies d’interférence réalisables à demi-DoF ayant la possibilité d’être les meilleures topologies en termes de taux réalisable. Enfin, cette thèse considère une étude de cas sur le TIM pour les réseaux sans fil à petite échelle, dans laquelle, nous considérons le problème TIM pour les réseaux à quatre utilisateurs en employant notre approche de construction de topologie d’interférence proposée. Ensuite, nous appliquons l’analyse des débits réalisables, proposée dans le cadre de la nouvelle approche de construction de topologie d’interférence, pour toutes les topologies d’interférence réalisables à demi-DoF, à la fois par partage orthogonal et IA, dans le problème TIM de réseaux sans fil à quatre utilisateurs.

 

 

Jury

  • Florian KALTENBERGER – Maître de Conférences HDR – EURECOM – Rapporteur
  • Iñaki ESNAOLA – Senior lecturer – University of Sheffield – Rapporteur
  • Ghaya REKAYA-BEN OTHMAN – Professeur des Universités – TELECOM PARIS – Examinatrice
  • Laurent CLAVIER – Professeur des Universités – TELECOM LILLE – Examinateur
  • Leonardo S. Cardoso – Maître de Conférence – Université de Lyon – Co-directeur
  • Jean-Marie Gorce – Professeur des Universités – Université de Lyon – Directeur

PhD Defence: “Deep learning based approaches for detection in physical layer wireless multiple access”, Cyrille Morin, Amphitheater, Chappe Building, 22th of July 2021 at 14:00 PM

The defense will be held in the Amphitheater, Chappe Building, and will be streamed live here: link

 

Title

Deep learning based approaches for detection in physical layer wireless multiple access

 

 

Abstract

Current trends point towards an accelerated augmentation of devices with a desire to access the shared radio spectrum, both due to the continued democratisation and capability augmentation of user facing radio devices, such as cellphones, computers, and especially wearables, but also to the deployment of connected objects and sensors. Technology, protocols, and legislation improvements increase the available frequency bands by opening new channels in the GHz range, but the density of devices is nevertheless expected to increase. Multiple access to a shared radio frequency resource leads to situations that are both complex to model, and to tackle with known algorithms, and it is true of detection tasks that arise in the physical layer of a wireless transmission. The class of deep learning algorithms is especially useful in this sort of situation without model, or with non tractable algorithms, as long as a large amount of labelled data is available to train the related neural networks. This thesis aims at adapting the deep learning tool to physical layer detection problems, in successive steps of a decoding chain. First with the problem of detecting the origin of a received packet, starting with hardware fingerprinting of a transmitting device, and extending it to a scenario with multiple active devices at the same time, detecting the set of active devices transmitting an explicit codeword. The next step after origin detection is bit detection, to decode transmitted messages. For that, deep learning is used to learn constellations allowing for an efficient bit detection in a multiple-access scenario, namely the two-user uplink NOMA. Data used to train the networks involved in this thesis are gathered both from simulated models, and from experimental implementations in the FIT/CorteXlab software defined radio test-bed.

 

 

Jury

  • Marco Di Renzo – Research Director – CentraleSupélec – Reviewer
    Symeon Chatzinotas – Professor – University of Luxembourg – Reviewer
    Marwa Chafii – Associate Professor – ENSEA – Examiner
    Catherine Douillard – Professor – IMT Atlantique – Examiner
    Christophe Moy – Professor – Université de Rennes 1 – President
    Leonardo S. Cardoso – Associate Professor – Université de Lyon – Co-supervisor
    Jakob Hoydis – Principal Research Scientist – Nvidia – Co-supervisor
    Jean-Marie Gorce – Professor – Université de Lyon – Supervisor

Félicitations à Razvan, reconnu « meilleur chercheur junior 2021 » du GdR RSD !

Chaque année le GdR RSD met en lumière des chercheurs. Cette année, le jury a sélectionné Razvan Stanica de l’équipe Agora du laboratoire CITI co-lauréats du prix du meilleur chercheur 2021 du GDR RSD dans la catégorie junior, aux côtés d’Alain Tchana (ENS / LIP).

En particulier, le jury a estimé que :

“Les deux candidats ont fait un travail exceptionnel, avec de nombreuses publications dans des conférences ou journaux de premier plan, une influence dans leur domaine comme en témoigne le nombre de citations de leurs travaux, une expérience établie de direction de recherche et d’animation scientifique et de fructueuses collaborations avec le monde universitaire et l’industrie.

Razvan Stanica a d’abord contribué au domaine des réseaux véhiculaires avant d’élargir ses thématiques de recherche aux stratégies de collecte de données des réseaux mobiles, à leur analyse pour caractériser les usages aussi bien que les performances et enfin aux architectures et protocoles réseaux en proposant une approche innovante de convergence du réseau d’accès et du réseau coeur. L’impact de son travail est reflété par un grand nombre de citations et par son leadership dans six projets de recherche, avec des partenaires académiques et industriels, dont un JCJC de l’ANR, qui débutera en 2021.”

Félicitations à Razvan pour l’obtention de ce prix et félicitations à l’équipe Agora pour l’environnement stimulant et aux moyens nécessaires à cet accomplissement !

 


HDR Defence: “Privacy issues in wireless networks, Every frame you send, they’ll be watching you.”, Mathieu Cunche, 2nd of June 2021 at 2PM

The defense will be streamed live here: link

 

Title

Privacy issues in wireless networks, Every frame you send, they’ll be watching you.

Abstract

A growing number of devices carried by users are equipped with wireless technologies such as Bluetooth and Wi-Fi which allow the seamless exchange of information between devices and the network infrastructure. Because they routinely emit wireless messages carrying identifiers and other technical artifacts in cleartext, these technologies expose users to privacy issues. Focusing on the data included in advertising messages, we identify and analyze the leakage of personal data, and study potential and existing countermeasures. More specifically, we try to answer the following questions: what are the privacy threats associated with wireless networks? Which solutions can be deployed to protect users against these threats? How efficient are current privacy protection implementations? We start by an analysis of privacy features of the two major wireless network standards: Wi-Fi and Bluetooth-Low-Energy. We focus our study on address randomization mechanisms, a recently adopted anti-tracking measure, and identify several issues related to implementation as well as standard specifications. To illustrate the diversity and complexity of the issues affecting these technologies, we present two representative cases of personal data leakage in wireless networks. First, leveraging the reverse-engineering of Continuity, a BLE-based protocol developed by Apple, we uncover a collection of personal data leakages affecting billions of devices worldwide. Finally, we present an abuse of Android Wi-Fi permission that can be used to bypass permissions and to infer personal data such as the location of the device. When confronted with those privacy issues, it becomes necessary to increase user protection by developing privacy-preserving mechanisms but most importantly by correctly implementing existing ones. Furthermore, it appears that standard specifications are key elements of a better protection, and it is thus of utmost importance to promote the integration of privacy protection in these standards.

 

Jury

    • Monsieur Noubir Guevara, Professeur, Northeastern University (Rapporteur)
    • Madame Fischer-Hübner Simone, Professeure, Karlstad University (Rapporteur)
    • Madame Guérin-Lassous Isabelle, Professeure, Université Claude Bernard Lyon 1
    • Monsieur Gorce Jean-Marie, Professeur, INSA-Lyon
    • Monsieur Zuniga Juan-Carlos, SigFox
    • Monsieur Anciaux Nicolas, Directeur de recherche, Inria, Université de Versailles/St-Quentin (Rapporteur)

Nouvelle équipe associée entre l’équipe Inria Agora du CITI/INSA Lyon et le LIRIMA / Université de Yaoundé (Cameroun)

Depuis Janvier 2021, et pour 3 ans, une nouvelle Equipe Associée a vu le jour entre l’équipe Inria Agora du CITI/INSA Lyon et le LIRIMA / Université de Yaoundé (Cameroun). Pilotée par Rodrigue Domga Komguem et Fabrice Valois, regroupant 6 permanents, les travaux de l’équipe IOTA(i) s’intéressent à la conception de protocoles d’auto-configuration, d’auto-organisation et au support de communications fiables pour l’Internet des Objets, dans un contexte de ville intelligente et d’agriculture connectée. Les fondamentaux des travaux réalisés s’appuieront sur des techniques d’apprentissages et d’apprentissage profond.

Contact :

    • Rodrigue Domga Komguem, domga.komguem@gmail.com
    • Fabrice Valois, fabrice.valois@insa-lyon.fr

CITI is hiring two PhD Students

PhD Student – Powering neural network based wake-up radio with radio-frequency energy harvesting

 

Supervision: Matthieu Gautier and Olivier Berder (IRISA), Guillaume Villemaud and Florin Hutu (CITI)
Keywords: Internet of things, Wake-up radio, Energy harvesting
Location: Shared between Lannion and Lyon (to be discussed)
Candidate skills: Signal processing and electronics are mandatory, backgrounds in digital communication, IoT, microcontroller programming are welcome
Application: Send CV, marks and motivation letter to matthieu.gautier@irisa.fr and guillaume.villemaud@ insa-lyon.fr

Context
Internet of Things (IoT) is becoming a reality. It will greatly impact our daily lives (city, housing, transportation, health, environment) and many economic sectors (agriculture, industry…). Unlicensed bands (868 MHz, 2.4 GHz) play an important role in this evolution with technologies like LoRa, SigFox or IEEE 802.15.4. However, energy consumption remains a major bottleneck, with many applications requiring the lifespan of objects to reach several years, even decades, without changing the batteries. Many efforts have been deployed to push the boundaries of energy autonomy, without however a full success.

The radio transceiver often turns out to be the most energy consuming part of a wireless node, due to both the transmitting and also receiving phases. For instance, initiating a communication requires that the source and the destination are awake at the same time. It can be difficult to plan and usually requires some highly penalizing signalling protocols. In short range multi-hop networks, ernergy consuming MAC strategies are implemented in order to synchronize the source and the destination. Low Power Wide Area Networks solved this issue by having always turned-on base stations using single hop communications and a simple ALOHA protocol, but this only works for the uplink. Wake-up receivers form an emerging technology, which allows continuous channel monitoring, while consuming orders of magnitude less power than traditional receivers. These receivers wake up a main transceiver using interrupts only when a specific signal is detected. Thus, fully asynchronous communication can be achieved, resulting in a huge decrease of energy waste. However, most wake-up receivers are still relying on low power microcontrollers that perform signal recognition but consume peak powers higher than 200 μW, making IoT nodes unable to reach their ultimate energy efficiency.

ANR U-Wake project aims to achieve a breakthrough in the field of IoT by developing a disruptive wake-up receiver solution based on (1) a bioinspired architecture achieved with an industrial CMOS technology (with transistors operating in deep sub-threshold regime) and (2) Electro Magnetic energy harvesting. The originality lies in the association of a Radio Frequency (RF) demodulator to a neuro-inspired detector and data- processing through a spiking neural network (SNN), resulting in a complete ultra-low power wake-up radio supplied with a voltage of a few 100 mV.

Objective of the PhD
The proposed receiver will be woken up when detecting a dedicated off-line learned sequence and implemented in a hardware fashion using an ultra-low power SNN. The main advantage of such a design is that it requires a few mW or less for the whole wake-up receiver. Furthermore, it can work in the 868 MHz or 2.4 GHz bands and has the ability to recognize different types of signals (on-off keying, BPSK or chirp spread spectrum modulation for instance). Requiring such a low consumption opens up the possibility to be powered using RF energy harvesting or Wireless Power Transfer, and opens the way to a wide range of application.

This PhD will focus on the energy efficiency of the proposed solution at both hardware and software levels. It will address the global node design, including RF energy harvesting unit, the integration of neuro-inspired circuits and related wake-up mechanisms, and will propose adequate power management policies.

More information here

 

PhD Student – Nouvelles stratégies de télé alimentation d’objets communicants et de drones en utilisant des techniques de formation de faisceau distribuée

 

Supervision: Guillaume Villemaud et Florin Hutu (CITI)
Keywords: radiocommunications, téléalimentation, IoT, drone, beamforming
Location: CITI laboratory, INSA Lyon, France
Application: Send CV, marks and motivation letter to florin-doru.hutu@insa-lyon.fr and guillaume.villemaud@ insa-lyon.fr

Context
Avec l’avancement des technologies semiconducteur et la réduction de la taille et du cout de fabrication des objets communicants, des conditions favorables ont été créées pour produire des capteurs communicants performants qui permettent le monitoring de différents phénomènes physiques, qui ont une autonomie accrue et qui impliquent une intervention humaine limitée voire inexistante. L’autonomie reste néanmoins un problème majeur pour ce type de capteurs, la durée de vie du réseau qui le forme lui étant étroitement liée. Plusieurs techniques ont été proposées et validées en ce sens, en partant de l’optimisation de la consommation énergétique au niveau bloc fonctionnel jusqu’à une optimisation au niveau protocole de communication. Le déploiement de tels capteurs est un enjeu majeur pour les systèmes civils et militaires et des techniques permettant la réduction de l’énergie consommée par ces objets se combinent avec des techniques de récupération d’énergie ambiante pour envisager des capteurs communicants sans source d’alimentation locale. De même la téléalimentation de micro-drones est un sujet en pleine émergence qui peut bénéficier des mêmes approches.

Objective of the PhD
Cette thèse adresse le problème de la synchronisation et de la mise en cohérence de phase des sources distribuées géographiquement. L’application envisagée est celle de la transmission de puissance sans fil en mettant en place des stratégies de type formation de faisceau distribuée. Ce projet souhaite aborder la problématique de la transmission de puissance sans fil vers un objet communicant à faible ressources énergétiques aussi bien de point de vue système de communication mais aussi du point de vue automatique ou le potentiel d’alimentation de micro-drones avec suivi de leur trajectoire. En automatique, le problème traité ici s’apparente à celui de la synchronisation d’un réseau de systèmes à retard ou bien à celui du suivi de trajectoire de référence. Les outils théoriques appliquées à ce scénario concret seront la commande de systèmes multi-agents, la commande de système à retard et l’observation de retard. Ces stratégies seront adaptées pour répondre aux contraintes matérielles des instruments de génération et d’analyse des signaux du laboratoire CITI. En effet, les « transcepteurs » vectoriels de signaux (VST) PXI-5646 de Nationals Instruments sont ciblés dans un premier temps pour ensuite passer à une échelle supérieure en utilisant la plateforme CorteXlab.

More information here

 

 


CITI seminar – El Hourcine Bergou (INRAE) – 09/04 at 15:00

Title:  Stochastic Three Points Method For Unconstrained Smooth Minimization

Date and Place: 9th April 2021 15:00 – link

Speaker: Dr El Hourcine Bergou (INRAE)

 

Abstract: 

In this work, we consider the unconstrained minimization problem of a smooth function in a setting where only function evaluations are possible. We design a novel randomized derivative-free algorithm—the stochastic three points (STP) method—and analyze its iteration complexity. At each iteration, STP generates a random search direction according to a certain fixed probability law. Our assumptions on this law are very mild: roughly speaking, all laws which do not concentrate all measure on any halfspace passing through the origin will work. Although, our approach is designed to not explicitly use derivatives, it covers some first order methods. For instance, if the probability law is chosen to be the Dirac distribution concentrated on the sign of the gradient, then STP recovers the Signed Gradient Descent method. If the probability law is the uniform distribution on the coordinates of the gradient, then STP recovers the Randomized Coordinate Descent Method.
The complexity of STP depends on the probability law via a simple characteristic closely related to the cosine measure which is used in the analysis of deterministic direct search (DDS) methods. Unlike in DDS, where $O(n)$ ($n$ is the dimension of the problem) function evaluations must be performed in each iteration in the worst case, our method only requires two new function evaluations per iteration. Consequently, while the complexity of DDS depends quadratically on $n$, our method depends linearly on $n$.

 

Biography:

Dr l Hourcine Bergou is a research scientist at INRAE. My research interests are in all areas that intersect with optimization, including algorithms, machine learning, statistics, and operations research. I am particularly interested in algorithms for large scale optimization including randomized and distributed optimization methods.

 


CITI seminar – Michael Barros (University of Essex, UK) – 01/04 at 14:00

Title:  Molecular Communications using Astrocytes for Boolean logic gates implementation in mammalian cells

Date and Place: 1st April 2021 14:00 – link

Speaker: Dr Michael Barros (University of Essex, UK)

 

Abstract: 

In this talk we will show the use of astrocytes to realize Boolean logic gates, through manipulation of the threshold of Ca2+ ion fows between the cells based on the input signals. Through wet-lab experiments that engineer the astrocytes cells with pcDNA3.1-hGPR17 genes as well as chemical compounds, we show that both AND and OR gates can be implemented by controlling Ca2+ signals that fow through the population. A reinforced learning platform is also presented in the paper to optimize the Ca2+ activated level and time slot of input signals Tb into the gate. This design platform caters for any size and connectivity of the cell population, by taking into consideration the delay and noise produced from the signalling between the cells. To validate the efectiveness of the reinforced learning platform, a Ca2+ signalling simulator was used to simulate the signalling between the astrocyte cells. The results from the simulation show that an optimum value for both the Ca2+ activated level and time slot of input signals Tb is required to achieve up to 90% accuracy for both the AND and OR gates. Our method can be used as the basis for future Neural–Molecular Computing chips, constructed from engineered astrocyte cells, which can form the basis for a new generation of brain implants.

 

Biography:

Dr Barros is an Assistant Professor (Lecturer) since June 2020 in the School of Computer Science and Electronic Engineering at the University of Essex, UK. He is also a MSCA-IF Research Fellow (part-time) at the Tampere University, Finland. He received the PhD in Computer Science at the Waterford Institute of Technology in 2016. He previously held multiple academic positions as a Research Fellow in the Waterford Institute of Technology, Ireland.
He has over 70 research peer-reviewed scientific publications in top journals and conferences such as Nature Scientific Reports, IEEE Transactions on Communications, IEEE Transactions on Vehicular Technology, in the areas of molecular and unconventional communications, biomedical engineering, bionano science and 6G. Since 2020, he is a review editor for the Frontiers in Communications and Networks journal in the area of unconventional communications. He also served as guest editor for the IEEE Transactions on Molecular, Biological and Multi-Scale Communications and Digital Communications Networks journals. He received the CONNECT Prof. Tom Brazil Excellence in Research Award in 2020. Dr Barros was awarded also the Irish Research Council’s (IRC) Government of Ireland Post-doc Fellow from 2016-2018 and the Enterprise Ireland’s (EI) Commercialization Funding from 2018-2019.

 


CITI seminar – Somantika Datta (Univ. Idaho, USA) – 18/02 at 14:00

Title: Construction and properties of certain real multi-angle tight frames

Date and Place: 18th February 2021 14:00 – link

Speaker: Prof. Somantika Datta (Univ. Idaho, USA)

 

Abstract: 

Frames are now standard tools in signal processing, and have applications ranging from compressed sensing, to communication systems and quantum sensing. Designing frames with some special structure such as equiangularity and tightness is highly desirable in applications. However, constructing equiangular tight frames (ETFs) with a given size in a specific dimension can be difficult or impossible in some cases. This leads one to consider the construction of frames with few distinct angles among pairs of frame vectors. In the special case of d+1 vectors in a d-dimensional space, it is well known that the vertices of a regular simplex will give an ETF. Using this, we will show a specific construction which, for a given dimension d and integer 1 < k ≤ d, gives a real unit norm tight frame such that the number of distinct angles among the vectors is bounded above by k. We will present several properties of this multi-angle tight frame. We also show how one can strategically choose subsets of such a multi-angle tight frame that will be equiangular or orthogonal. This property is meaningful in the context of erasures. We will also discuss a connection between certain unit norm tight frames with three angles and adjacency matrices of regular graphs.

 

Biography:

Somantika Datta is an associate professor of mathematics at the University of Idaho. She received a Ph.D. in mathematics from the University of Maryland, College Park. This was followed by postdoctoral positions at Arizona State University and Princeton University. Her research interests lie in the area of applied harmonic analysis with focus on frame theory and applications in signal processing.

 


CITI seminar – Daryus Chandra (University of Southampton, UK) – 11/02 at 14:00

Title: Quantum Communications over Noisy Entanglement

Date and Place: 11th February 2021 14:00 – link

Speaker: Dr Daryus Chandra (University of Southampton, UK)

 

Abstract: 

Within the Quantum Internet framework, multiple quantum devices are interconnected via pre-shared maximally-entangled quantum states for enabling various applications, including the on-demand classical and quantum communication. Hence, the pre-shared entanglement, which is constituted by the EPR pair, can be viewed as the primary consumable resources within the Quantum Internet. However, the generation and the distribution of the EPR pairs are subject to quantum decoherence imposed by the quantum channels, which will manifest as quantum errors. Similar to the classical domain, the quantum errors imposed by the quantum channels can be mitigated using quantum error-correction codes. In this talk, we will explore two approaches for achieving reliable quantum communication over noisy entanglement by incorporating quantum error-correction codes. More specifically, the first approach is constituted by the consecutive steps of quantum entanglement distillation followed by quantum teleportation, while the second approach can be viewed as the direct quantum communication over noisy entanglement. We will also discuss the pros and the cons of each approach while examining their compatibilities for a broader range of applications for the Quantum Internet framework.

 

Biography:

Daryus Chandra is a research fellow at the Next-Generation Wireless Research Group, School of Electronics and Computer Science, University of Southampton, UK. He received the B.Eng. and M.Eng. degree from the Department of Electrical Engineering and Information Technology, Universitas Gadjah Mada, Indonesia, in 2013 and 2014, respectively. He obtained his PhD with the Next-Generation Wireless Research Group, School of Electronics and Computer Science, University of Southampton, UK, in 2020. He returned to Southampton in 2021 after completing a one-year postdoctoral research fellowship at Quantum Internet Research Group, University of Naples Federico II, Italy.