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 !


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)



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 $n$.



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)



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.



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)



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.



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)



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.



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.


PhD Defence: “De l’évaluation des performances Wi-Fi à la mobilité contrôlée pour les réseaux de drones”, Remy Grünblatt, 8th of January 2021 at 14:00 PM

The defense will be streamed live here: link



De l’évaluation des performances Wi-Fi à la mobilité contrôlée pour les réseaux de drones



La mobilité dans les réseaux de télécommunications est souvent considérée comme un problème qu’il faut résoudre : un appareil mobile sans fil doit adapter ses paramètres de transmission afin de rester connecté à son ou ses homologues, car le canal évolue avec les mouvements de l’appareil. Les drones, qui sont des véhicules aériens sans pilote, ne font pas exception. En raison de leur grande liberté de mouvements, de leur mobilité tridimensionnelle, et ce dans des environnements aussi nombreux que variés, de leur charge utile limitée et de leurs contraintes énergétiques, et en raison du large éventail de leurs applications dans le monde réel, les drones représentent de nouveaux objets d’étude passionnants dont la mobilité est un défi. Pourtant, la mobilité peut aussi être une chance pour les réseaux de drones, surtout lorsque nous pouvons la contrôler. Dans cette thèse, nous explorons comment la mobilité contrôlée peut être utilisée pour augmenter les performances d’un réseau de drones, en mettant l’accent sur les réseaux IEEE 802.11 et les petits drones multi-rotor. Nous décrivons d’abord comment la mobilité est traitée dans les réseaux 802.11, c’est-à-dire en utilisant des mécanismes d’adaptation de débit, puis nous effectuons l’ingénierie inverse de l’algorithme d’adaptation de débit utilisé dans le chipset Wi-Fi du drone Intel Aero. L’étude de cet algorithme d’adaptation de débit, de manière à la fois expérimentale et par simulation, grâce à son implémentation dans le simulateur de réseau NS-3, permet de le comparer à d’autres algorithmes bien connus. Cette étude met en évidence l’importance de ces algorithmes pour les réseaux de drones, en lien avec leur mobilité, et la différence de comportement de chaque nœud en résultant. Par conséquent, une solution de mobilité contrôlée visant à améliorer les performances du réseau ne peut pas supposer beaucoup du comportement des algorithmes d’adaptation de débits. En outre, les applications des réseaux de drones sont diverses, et il est difficile d’imposer des contraintes de mobilité sans devenir incompatible avec un pan complet d’applications. Nous proposons donc une solution de mobilité contrôlée qui exploite le diagramme de rayonnement de l’antenne des drones. Cet algorithme est évalué grâce à outil de simulation développé pour l’occasion, permettant la simulation d’antennes et de drones, basé sur NS-3. Cette solution, qui fonctionne avec n’importe quel algorithme d’adaptation de débit, est distribuée, et ne nécessite aucune coordination globale ou communication spécifique qui pourrait s’avérer coûteuses. Elle ne nécessite pas non plus un contrôle complet de la mobilité du drone comme le requièrent les solutions de mobilité contrôlée existantes, ce qui rend cette solution compatible avec diverses applications.




  • Mme. Nathalie MITTON, Directrice de recherche à INRIA Lille Nord – Europe, Rapportrice
  • Mr. Enrico NATALIZIO, Professeur des universités au Technology Innovation Institute – Abu Dhabi, Rapporteur
  • Mme. Laure GONNORD, Maître de conférences à l’université Lyon 1 Claude Bernard – Lyon, Examinatrice
  • Mr. André-Luc BEYLOT, Professeur des universités à l’ENSEEIHT – Toulouse, Examinateur
  • Mr. Franck ROUSSEAU, Maître de conférences à Grenoble INP-Ensimag – Grenoble, Examinateur
  • Mme. Isabelle GUÉRIN-LASSOUS, Professeure des universités à l’université Lyon 1 Claude Bernard – Lyon, Directrice de thèse
  • Mr. Olivier SIMONIN, Professeur des universités à l’INSA de Lyon, Codirecteur de thèse

CITI seminar – Lucien Etienne (IMT Lille-Douai) – 17/12 at 14:00

Title: Self trigger co-design using LASSO regression

Date and Place: 17th December 2020 14:00 – link

Speaker: Lucien Etienne (IMT Lille-Douai)



Networked systems have become more and more pervasive in many modern industrial application. A good justification for their deployment is that they can be cheaper/faster to set in place as well are scalable while also enabling lower maintenance cost. In the past decade a new paradigm has been developed where the controller is not sampled periodically (i.e. with a time–triggered policy), but rather sampled when some condition has been met (Usually a stability or performance criterion being violated). After recalling some general element on classical control scheme ( Linear Quadratic regulator and model predictive control) In this talk, the control of a linear time invariant system with self triggered sampling is considered .
In order to address the controller computation and the future sampling schedule a sparse optimization problem will be considered. A relaxation of the optimal self triggered control can be formulated as a LASSO regression. Using the properties of the solution of the Lasso regression it is shown how to obtain a controller ensuring practical or asymptotic stability while reducing sampling of the control action.



Dr. Lucien Etienne received a M.Sc. Degree in applied mathematics at the INSA Rouen in 2012 and a joint Ph.D. in automatic control from the university of L’aquila and the university of Cergy-Pontoise in 2016. From 2016 to 2017 he was a post doctoral researcher at Inria Lille-Nord Europe. Since 2017 He is an associate professor at Institut Mines-Télécom Lille Douai. His research interests include switched and hybrid systems, observer synthesis and sampled data systems.


PhD Defence: “Impulsive and Dependent Interference in IoT Networks”, Ce Zheng, 8th of December 2020 at 14:00PM

The defense will be streamed live here: link



Impulsive and Dependent Interference in IoT Networks


The number of devices in wireless IoT networks is now rapidly increasing and is expected to continue growing in the coming years.
To support this massive connectivity, a number of new technologies, collectively known as LPWAN, have been developed. Many devices in LPWANs limit their transmissions by duty cycle constraints; i.e., the proportion of time allocated for transmission. For nearby wireless networks using the same time-frequency resources, the increasing number of devices leads to a high level of unintended signals, known as interference.

In this thesis, we characterize the statistics of interference arising from LPWANs, with a focus on protocols related to NB-IoT and emerging approaches such as SCMA. Such a characterization is critical to improve signal processing at the receiver in order to mitigate the interference. We approach the characterization of the interference statistics by exploiting a mathematical model of device locations, signal attenuation, and the access protocols of individual interfering devices. While there has been recent work developing empirical models for the interference statistics, this has been limited to studies of the interference power, which has limited utility in receiver design. The approach adopted in this thesis has the dual benefits of providing a model for the amplitude and phase statistics and while also yielding insights into the impact of key network parameters. The first contribution in this work is to revisit interference in a single subcarrier system, which is widely used in current implementations of IoT networks. A basic model in this scenario distributes interfering devices according to a homogeneous Poisson point process. It has been long known that the resulting interference is well approximated via an alpha-stable model, rather than a Gaussian model. In this work, the \alpha-stable model is shown via theoretical and simulation results to be valid in a wider range of models, including the presence of guard zones, finite network radii, and non-Poisson point processes governing device locations. The second contribution in this thesis is the study, for the first time, of interference statistics in multi-carrier IoT networks, including those that exploit NB-IoT and SCMA. Motivated by the results in the single subcarrier setting, a multivariate model based on alpha-stable marginals and copula theory is developed. This model is verified by extensive simulations and further justified via a new, near-optimal, parameter estimation algorithm, which has very low complexity. The third part of this thesis applies the characterizations of the interference statistics to receiver design. A new design for nonlinear receivers is proposed that can significantly outperform the state-of-the-art in multi-carrier IoT systems. When receivers are restricted to be linear, the optimal structure is identified and the bit error rate characterized. Numerical results also illustrate how the average quantity of data interfering devices are required to transmit affects the receiver performance.



  • Prof. Claude Oestges (Ecole Polytechnique de Louvain, Belgium)
  • Assis. Prof. Lina Mroueh (Institut Supérieur d’Electronique de Paris, France)
  • Assoc. Prof. Mylene Pischella (Conservatoire National des Arts et Métiers, France)
  • Prof. Jean-François Hélard (INSA Rennes)
  • Assoc. Prof. Troels Pedersen (Univ. Aalborg, Denmark)
  • Prof. Gareth Peters (Heriot-Watt, UK)

CITI seminar – Ignacio Rodriguez (Aalborg University) – 10/12 at 14:00

Title: Experimental Research on Wireless Systems for Industrial Automation

Date and Place: 10th December 2020 14:00 – link to come

Speaker: Ignacio Rodriguez (Aalborg University)

Host: Maracas



The fourth industrial revolution – or Industry 4.0 (I4.0), will introduce major shifts in the way that products will be manufactured in the future. By integrating different cyberphysical systems (CPS), Internet-of-Things (IoT) technologies and cloud computing; the factories of the future will be equipped with highly flexible manufacturing equipment offering also a high reliability, thereby increasing the overall production throughput. One of the key enablers for such revolution is wireless communication. By replacing existing wirelines in the current industrial equipment with wireless technologies, the overall cost of deployment will be reduced, while at the same time a faster re-configuration of the smart production facilities will be enabled. Moreover, the use of wireless technologies will also allow for new industrial use cases requiring full mobility support such as autonomous robots moving items over different workstations in the factory for the sake of manufacturing customized products. During this talk, the AAU Industrial Automation Applied Research Flow will be introduced and illustrated with application examples detailing the different steps from understanding the needs of a factory and the specific communication requirements of industrial use cases; to the final deployment and optimization of the wireless solutions.



Ignacio Rodriguez received the B.Sc. and M.Sc. degrees in Telecommunication Engineering from University of Oviedo, Spain, and the M.Sc. degree in Mobile Communications and the Ph.D. degree in Wireless Communications from Aalborg University, Denmark. Since December 2016, he has been a Postdoctoral Researcher at the same institution, where he is currently coordinating the Industry 4.0 experimental research activities at the Wireless Communication Networks Section and the AAU 5G Smart Production Lab in collaboration with the Department of Materials and Production. Ignacio is also an External Research Engineer with Nokia Bell Labs, where he is involved in 3GPP and ITU-R standardization activities. His research interests are mainly related to radio propagation, channel modeling, radio network planning and optimization, machine-to-machine communications, ultra-reliable and low-latency communications, 5G and Industrial IoT. He is a co-recipient of the IEEE VTS 2017 Neal Shepherd Memorial Best Propagation Paper Award, and in 2019, he was awarded with the 5G-prize by the Danish Energy Agency and the Danish Society of Telecommunication Engineers.


CITI seminar – Howard Yang (Zhejiang University, China) – 26/11 at 14:00

Title: Spatiotemporal Modeling of Wireless Networks

Date and Place: 26 / 11 / 2020 14:00 – https://bbb.tuxlab.net/b/mal-ngv-xm6-qgd

Speaker: Howard Yang (Zhejiang University, China)

Host: Maracas



The rapid growth of wireless applications has brought along new challenges for the next generation network, which is expected to manage a massive number of devices in real-time under a highly dynamic environment. To give an adequate response, it is of necessity to develop an analytical model with which designers can build intuitions, grasp insights, and identify critical issues. In this talk, I will describe a framework for the analysis of large-scale wireless networks in which the transceivers interact with each other through the interference they caused and hence are correlated in both space and time. The analysis straddles stochastic geometry and queueing theory to cope with the issues of spatially interacting queues, and arrive at handy expressions for the SINR distribution. As a result, a wide variety of systems/architecture can be devised based on this theoretical foundation. Specifically, I will demonstrate how to adopt such a mathematical model to the analysis of two particular network metrics, i.e., the packet delay and age of information, and the subsequent network deployment guidelines based on the analytical results.



Howard Hao Yang received the B.Sc. degree in Communication Engineering from Harbin Institute of Technology (HIT), China, in 2012, and the M.Sc. degree in Electronic Engineering from Hong Kong University of Science and Technology (HKUST), Hong Kong, in 2013. He earned the Ph.D. degree in Electrical Engineering from Singapore University of Technology and Design (SUTD), Singapore, in 2017, and stayed three years as a postdoc. He is now an assistant professor with the ZJU-UIUC Institute, Zhejiang University. Dr. Yang’s background also features appointments at the Princeton University in 2018 – 2019, and the University of Texas at Austin in 2015 – 2016. His research interests cover various aspects of wireless communications, networking, and signal processing, currently focusing on the modeling of next-generation wireless networks, age of information, and federated learning.