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

 

Title

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

 

Abstract

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.

 

 

Jury

  • 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)

 

Abstract: 

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.

 

Biography:

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

 

Title

Impulsive and Dependent Interference in IoT Networks

Abstract

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.

 

Jury

  • 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

 

Abstract: 

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.

 

Biography:

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

 

Abstract: 

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.

 

Biography:

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.

 


CITI seminar – Jean Marie GORCE (Citi) – 07/07 at 14:00

Title: On computing individual exposure risk to a pandemia with BLE-RSSI measures

Date and Place: 07 / 07 / 2020 14:00

Speaker: Jean Marie GORCE (Citi)

Place: https://bbb.tuxlab.net/b/mal-eef-nrd

 

Abstract: Tracking how Covid-19 spreads over a population is a critical aspect that may aid relaxing lockdown conditions. Most of current solutions (e.g. as proposed in the European project PEPP-PT, the French application Stopcovid, the GAEN (Google-Apple Exposure Notification) ) rely on the RSSI signals obtained with Bluetooth Low Energy (BLE) HELLO messages. In this talk, we describe an algorithm which is complient with the constraints imposed by the rules and parameters of the ROBERT protocol developed by the Privatics team (Inria) and used in the Stopcovid application. Underlying the algorithm is mathematical modeling of the physical wireless communication link, based on real-life BLE RSSI traces. In particular, the algorithm is evaluated on experimental data obtained in the PEPP-PT project (April 2020) and lead by the Fraunhoffer institute, and experimental data aquired by the Stopcovid consortium (May, 2020) lead by Inria, both providing a large number of device-to-device BLE RSSI traces in realistic scenarios.

 

 


CITI seminar – Mario Zanon (IMT Lucca) – 30/06 at 14:00

Title: Optimal Control, MPC, and Reinforcement Learning

Date and Place: 30 / 06 / 2020 14:00

Speaker: Mario Zanon (Assistant Professor, IMT Lucca, Italy)

Host: Maracas

 

Abstract: Data-driven control approaches such as Reinforcement Learning (RL) mitigate the issue of model construction and controller tuning by learning directly the (optimal) control law from data. While stunning results have been obtained, RL cannot provide stability nor safety guarantees. Additionally, while partial information on the system is usually available, it can be hard to use it within RL. Model Predictive Control (MPC) is an advanced control technique able to deal with nonlinear systems subject to constraints. The main idea of MPC is to use a mathematical model of the process to predict its future behavior and minimize a given performance index. The advantages of MPC are numerous, as it makes it relatively easy to handle various difficulties in control design, such as dealing with constraints, nonlinear and hybrid dynamics, etc. One of the main drawbacks of MPC is that control performance is highly dependent on the predictive ability of the model. In this seminar, we will discuss how RL and MPC can be combined with the aim of benefitting from the advantages of each while limiting the drawbacks of both. We will introduce the two techniques and present some recent theoretical results, supported by simulation results.

 

Biography:
Mario Zanon received the Master’s degree in Mechatronics from the University of Trento, and the Diplôme d’Ingénieur from the Ecole Centrale Paris, in 2010. After research stays at the KU Leuven, University of Bayreuth, Chalmers University, and the University of Freiburg he received the Ph.D. degree in Electrical Engineering from the KU Leuven in November 2015. He held a Post-Doc researcher position at Chalmers University until the end of 2017 and is now Assistant Professor at the IMT School for Advanced Studies Lucca. His research interests include numerical methods for optimization, economic MPC, reinforcement learning and optimal control and estimation of nonlinear dynamic systems, in particular for aerospace and automotive applications.

 


CITI seminar – Ioannis Krikidis (Univ. Cyprus) – 13/02 at 11:30

Title: Wireless Powered Communications: Overview, Recent Results, and Challenges

Date and Place: 13 / 02 / 2020 10:30 in TD-C

Speaker: Ioannis Krikidis (Univ. Cyprus)

Host: Maracas

 

Abstract:
Conventional energy-constrained wireless systems such as sensor networks are powered by batteries and have limited lifetime. Wireless power transfer (WPT) is a promising technology for energy sustainable networks, where terminals can harvest energy from dedicated electromagnetic radiation through appropriate electronic circuits. The integration of WPT technology into communication networks introduces a fundamental co-existence of information and energy flows; radio-frequency signals are used in order to convey information and/or energy. The efficient management of these two flows through sophisticated networking protocols, signal processing/communication techniques and network architectures, gives rise to a new communication paradigm called wireless powered communications (WPC). In this talk, we discuss the principles of WPC and we highlight its main network architectures as well as the fundamental trade-off between information and energy transfer. Several examples, which deal with the integration of WPC in modern communication systems, are presented.

 

Biography:
Dr. Ioannis Krikidis received the diploma in Computer Engineering from the Computer Engineering and Informatics Department (CEID) of the University of Patras, Greece, in 2000, and the M.Sc and Ph.D degrees from Ecole Nationale Superieure des Telecommunications (ENST), Paris, France, in 2001 and 2005, respectively, all in electrical engineering. From 2006 to 2007 he worked, as a Post-Doctoral researcher, with ENST, Paris, France, and from 2007 to 2010 he was a Research Fellow in the School of Engineering and Electronics at the University of Edinburgh, Edinburgh, UK. He is currently an Associate Professor at the Department of Electrical and Computer Engineering, University of Cyprus, Nicosia, Cyprus. His current research interests include wireless communications, cooperative networks, 4G/5G communication systems, wireless powered communications, and secrecy communications. I. Krikidis is an IEEE Fellow (class 2019) and he has received the prestigious ERC consolidator grant.

 


CITI seminar – Mari Kobayashi (TU Munich) – 13/02 at 10:30

Title: Joint State Sending and Communications: Theory and Vehicular Applications

Date and Place: 13 / 02 / 2020 10:30 in TD-C

Speaker: Mari Kobayashi (TU Munich)

Host: Maracas

 

Abstract:
We consider a communication setup where transmitters wish to simultaneously sense network states and convey messages to intended receivers. The scenario is motivated by joint radar and vehicular communications where the radar and data applications share the same bandwidth. First, I present a theoretical framework to characterize the fundamental limits of such a setup for memoryless channels with i.i.d. state sequences. Then, I present our recent work on joint radar and communication using Orthogonal Time Frequency Space (OTFS). Although restricted to a simplified scenario with a single target, our numerical examples demonstrated that two modulations provide as accurate radar estimation as Frequency Modulated Continuous Waveform (FMCW), a typical automotive radar waveform, while providing a non-negligible communication rate for free.

 

Biography:
Mari Kobayashi received the B.E. degree in electrical engineering from Keio University, Yokohama, Japan, in 1999, and the M.S. degree in mobile radio and the Ph.D. degree from École Nationale Supérieure des Télécommunications, Paris, France, in 2000 and 2005, respectively. From November 2005 to March 2007, she was a postdoctoral researcher at the Centre Tecnològic de Telecomunicacions de Catalunya, Barcelona, Spain. In May 2007, she joined the Telecommunications department at CentraleSupélec, Gif-sur-Yvette, France, where she is now a professor. She is the recipient of the Newcom++ Best Paper Award in 2010, and IEEE Comsoc/IT Joint Society Paper Award in 2011, and ICC Best Paper Award in 2019. Since September 2017, she is on a sabbatical leave at Technical University of Munich (TUM) as an Alexander von Humboldt Experienced Research Fellow (till April 2019) and August-Wihelm Scheer Visiting Professor (since August 2019).

 


PhD Defence: “Simultaneous Information and Energy Transmission”, Nizar Khalfet, Emilie du Chatelet Amphitheater, INSA, 13th of February 2020 at 14h

Title

Simultaneous Information and Energy Transmission

Abstract

In this thesis, the fundamental limits of simultaneous information and energy transmission (SIET) are studied from two perspectives: the asymptotic and non-asymptotic block-length regimes. In the asymptotic block-length regime, the fundamental limits on SIET in the two-user Gaussian interference channel (G-IC) with and without feedback are characterized. More specifically, an achievable and converse region in terms of information and energy transmission rates (in bits per channel use and energy-units per channel use, respectively) are identified. In both cases, with and without feedback, an achievability scheme based on power-splitting, common randomness, rate splitting, block-Markov superposition coding, and backward decoding is presented. Finally, converse regions for both cases are obtained using some of the existing outer bounds on information transmission rates, as well as a new outer bound on the energy transmission rate. For the finite block-length regime, the case of a transmitter simultaneously sending information to a receiver and energy to an energy harvester through the binary symmetric channel has been studied. Given a finite number of channel uses (latency constraint) as well as tolerable average decoding error probability and energy shortage probability (reliability constraints), two sets of information and energy

transmission rates are presented. One consists in rate pairs for which the existence of at least one code achieving such rates under the latency and reliability constraints is proved (achievable region). The second one consists in a set whose complement contains the rate pairs for which there does not exist a code capable of achieving such rates (converse region). These two sets approximate the information-energy capacity region, which allows analyzing the trade-offs among performance, latency, and reliability in SIET systems.

 

 

Jury

  • Dr. Samson Lasaulce, CNRS, France. Reviewer.
  • Dr. Ioannis Krikidis, University of Cyprus, Cyprus. Reviewer.
  • Dr. Marie Kobayashi, CentraleSupelec, France. Examiner.
  • Dr. Jean-Marie Gorce, INSA de Lyon, France. Supervisor.
  • Dr. Samir M. Perlaza, INRIA, France. Advisor.