Archives des séminaires

In the automotive, softwares are more and more present  However, during the development lifecycle, errors and flaws can be introduced and lead to failures. Due to the lack of automatic and formal means, verifying that the softwares are bug free and compliant with the requirements is challenging. In this presentation we propose an approach inspired by formal methods that helps analyse and validate the developped softwares.

Pandoc is a computer program written in Haskell (a functional programming language) that 

converts documents from one of many possible input formats (docx, epub, html, json, latex, 

markdown, odt...) and to one of many possible output formats (beamer, docx, epub, html, 

latex, markdown, odt, pdf, pptx, slidy...) 

In this talk we will present pandoc, its internal representation of documents and its 

processing flow. We will then show how to produce beamer/PDF or HTML/javascript presentations

from markdown inputs. Finally, we will show how the lua scripting language, the pandoc templates 

and the beamer templates can be used to customize pandoc in order to produce advanced presentations 

in the Telecom Paris style.

in 3C14 at 10am

Abstract:

One of the next frontiers in communication technology is to re-think methods of sharing
spectrum among wireless transmitters. In this talk, I will discuss recent results on
characterizing the fundamental tradeoff between the density of users (ratio of active users and the number of degrees of freedom available per frame) and 
the minimal required energy-per-bit (Eb/N0). In the regime of interest for the Internet-of-Things, 
the payload of each user is about 100 data bits. This is too small for the asymptotic Shannon theory to provide any guidance and thus we needed to develop new tools for analysis.
A surprising discovery is existence of coded-access schemes that are able to almost perfectly reject
the multi-user interference, so that increasing the density of users
(without increasing space-time-frequency resources) does not lead to
any deterioration of service. Practically important is that known
MAC architectures are not capable of attaining this effect. A similar analysis and effects
arise in the problem of (unsourced) random-access over the AWGN channel, which we will
discuss as well.

in A301 at 2pm

Abstract:

Suppose that Alice wants to convey to Bob the results of k iid fair coin flips, using n times an iid binary symmetric channel (that is, in each use Alice's inout is flipped with probability e). We measure the performance by the expected Hamming distortion D, i.e., the probability that Bob's guess of a coin flip after seeing the channel outputs is wrong. Let D*(k, r, e) be the optimal attainable expected distortion, where r=n/k. For any fixed r, as k tends to infinity the optimum is attained by the separation principle: Alice and Bob should use the concatenation of optimal compression and digital communication. However, other approaches, known collectively as joint source-channel coding (JSCC) may be superior in terms of finite-blocklength performance (D* for limited k) and robustness (the performance when Alice does not know e). For r=1, a simple scalar (k=1) scheme attains D* universally over all e, but in general there are many open questions regarding the fundamental bounds of JSCC. We present some old and new results, and in particular show a surprising connection: an impossibility bound on robustness leads to a finite-blocklength bound.
Based in part on joint work with Or Ordentlich and Yury Polyanskiy.

in A301 at 10am

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.

at 10.15apm in Amphi Grenat

Abstract:  

Wireless technology has enormous potential to change the way we live, work, and play over the next several decades. Future wireless networks will support 100 Gbps communication between people, devices, and the “Internet of Things,” with high reliability and uniform coverage indoors and out. New architectures including edge computing will drastically enhance efficient resource allocation while also reducing latency for real-time control. The shortage of spectrum will be alleviated by advances in massive MIMO and mmW technology, and breakthrough energy-efficiency architectures, algorithms and hardware will allow wireless networks to be powered by tiny batteries, energy-harvesting, or over-the-air power transfer. There are many technical challenges that must be overcome in order to make this vision a reality. This talk will describe our recent research addressing some of these challenges, including new modulation and detection techniques robust to rapidly time-varying channels, blind MIMO decoding strategies, machine learning equalization and source-channel coding, as well as “fog”-optimization of resource allocation in cellular systems.

Biography:

Mardi 17 septembre, 14H, Télécom Paris, Amphi B312, 46 rue Barrault, Paris 13

 Future wireless networks are expected be more than allowing people, mobile devices, and objects to communicate with each other. Future wireless networks will constitute a distributed intelligent communications, sensing, and computing platform. Small cells, Massive MIMO, millimeter-wave communications are three fundamental approaches to meet the requirements of 5G wireless networks. Their advantages are undeniable. The question is, however, whether these technologies will be sufficient to meet the requirements of future wireless networks that integrate communications, sensing, and computing in a single platform. Wireless networks, in addition, are rapidly evolving towards a softwaredefined design paradigm, where every part of the network can be configured and controlled via software. In this optimization process, however, the wireless environment remains an uncontrollable factor: It remains unaware of the communication process undergoing within it. Apart from being uncontrollable, the environment has a negative effect on the communication efficiency: signal attenuation limits the network connectivity, multi-path propagation results in fading phenomena, reflections and refractions from objects are a source of uncontrollable interference. In the recent period, a brand-new technology, which is referred to as Reconfigurable Intelligent Surfaces (RISs), was brought to the attention of the wireless community. The wireless future that can be envisioned by using this technology consists of coating every environmental object with man-made reconfigurable surfaces of electromagnetic material (software-defined reconfigurable metasurfaces) that are electronically controlled with integrated electronics and wireless communications. In contrast to any other technology currently being used in wireless networks, the distinctive characteristic of the RISs consists of making the environment fully controllable by the telecommunication operators, by allowing them to shape and control the electromagnetic response of the objects distributed throughout the network. The RISs are a promising but little understood technology that has the potential of fundamentally changing how wireless networks are designed today. In this talk, we will discuss the potential of RISs in 6G wireless networks.

assive UHF RFID localisation : state of the art and needed technology breakthrough

Jeudidi 12 septembre, 14H, Télécom Paris, Amphi SAPHIR, 46 rue Barrault, Paris 13

Passive UHF RFID tags have reached a very low cost level <0.05 € and start to be massively deployed in various sectors of activity (20 billions units sold in 2018). The readers able to acquire the data contained in the tags are mainly hand held devices, with operators scanning the products at a distance of less than 0.5 m, but also fixed devices installed at doorways, which dynamically read tags happening to pass in front of them.

In the future it will be extremely useful, and is one of the big challenges, to achieve Real Time Location System (RTLS) in order to carry out the automatic inventory of static tags distributed on a large area (i.e. 100 m²), typically a stockroom with hundreds of meters of shelves containing RFID tagged products. To that aim, an innovative RTLS will be presented in this talk, based on a bistatic system with:
- one single central Rx point, called HotSpot (HS), able to read all tags which have been powered up
- hundreds of distributed wireless transmitters, called Power Nodes (PN), placed inside the shelves and transmitting the maximum allowed power in order to provide sufficient energy to the surrounding tags
- tags operating in backscattering mode toward the HS, when they are powered up

The HS+PN combination enables successful reads in excess of 99.9% (i.e. a handful of no reads, out of a typical stock of 5000 items) and a localisation accuracy better than 0.5 m for 90% of the tags. The principle allowing to achieve these results is, for a given tag that in practice has been powered up by typically 10 PN transmitters, to localise it onto the one generating the largest received signal at the HS. However the accuracy is less than 1m for 10% of the tags, the reason being still under investigation although it seems to involve the propagation channel between the PN transmitter and the tag. One promising direction for improvement is machine learning, since a large amount of training data are available, thye system typically generating daily 1million tag data. Indeed it turns out that the well known KNN algorithm (K Nearest Neighbors), a "lazy" machine learning process, already delivers good results in some RFID applications.

Mardi 9 juillet, 11H, Télécom Paris, Amphi JADE, 46 rue Barrault, Paris 13

Based on wave chaos theory, statistical methods have been successfully developed and used to devise simulation tools that characterise the electromagnetic energy flow through large structures with a reasonable computational effort. A specific model, the random coupling model, which describes the high-frequency excitation of irregular environments, is derived and applied to cavity problems of practical interest in wireless systems.  Results are relevant in wireless channels in telecommunications, wavefront shaping in imaging and radars, reverberation chambers in electromagnetic compatibility, and microwave applicators in material processing engineering.

in A301 at 10am

Abstract

The data traffic has grown dramatically over the past few years mainly due to video streaming. By utilizing the storage capabilities of the network nodes, caching can greatly improve the spectral efficiency and reduce the transmission latency (delay). In this talk, we develop and analyze caching schemes for two types of nontrivial networks: two-layer relay network and server-aided D2D network. For both networks, our schemes are order optimal and can further reduce the transmission delay compared to the previously known caching schemes. Moreover, for the two-layer 2-relay network, we surprisingly find that if each relay’s caching size equals to 38.2% of full library’s size, increasing the relay’s caching memory CANNOT reduce the transmission delay. For the server-aided D2D network, our scheme achieves a cooperation gain and aparallel gain by fully exploiting user cooperation and optimally allocating communication loads among the server and users.

Vendredi 5 juillet, 14H, Télécom Paris, Amphi B310, 46 rue Barrault, Paris 13

Rick S. Blum
IEEE Fellow, IEEE Signal Processing Society Distinguish Lecturer,
Robert W. Wieseman Endowed Professor of Electrical Engineering
Electrical and Computer Engineering Dept., Lehigh University

The Internet of Things (IoT) improves pervasive sensing and control capabilities via the aid of modern digitial communication, signal processing and massive deployment of sensors. The employment of low-cost and spatially distributed IoT sensor nodes with limited hardware and battery power, along with the low required latency to avoid unstable control loops, presents severe security challenges.  Attackers can modify the data entering or communicated from the IoT sensors which can have serious impact on any algorithm using this data for inference.  In this talk we describe how to provide tight bounds (with sufficient data) on the performance of the best algorithms trying to estimate a parameter from the attacked data and communications under any assumed statistical model describing how the sensor data depends on the parameter before attack.  The results hold regardless of the estimation algorithm adopted which could employ deep learning, machine learning, statistical signal processing or any other approach.  Example algorithms that achieve performance close to these bounds are illustrated.  Attacks that make the attacked data useless for reducing these bounds are also described.  These attacks provide a guaranteed attack performance in terms of the bounds regardless of the algorithms the estimation system employs.  References are supplied which provide various extensions to all the specific results presented and a brief discussion of applications to IEEE 1588 for clock synchronization is provided.

Rick S. Blum received a B.S.E.E from Penn State in 1984 and an M.S./Ph.D in EE from the University of Pennsylvania in 1987/1991. From 1984 to 1991 he was with GE Aerospace. Since 1991, he has been at Lehigh University. His research interests include signal processing for smart grid, communications, sensor networking, radar and sensor processing. He was an AE for IEEE Trans. on Signal Processing and for IEEE Communications Letters. He has edited special issues for IEEE Trans. on Signal Processing, IEEE Journal of Selected Topics in Signal Processing and IEEE Journal on Selected Areas in Communications. He was a member of the SAM Technical Committee (TC) of the IEEE Signal Processing Society. He was a member of the Signal Processing for Communications TC of the IEEE Signal Processing Society and is a member of the Communications Theory TC of the IEEE Communication Society. He was on the awards Committee of the IEEE Communication Society. Dr. Blum is a Fellow of the IEEE, an IEEE Signal Processing Society Distinguished Lecturer (twice), an IEEE Third Millennium Medal winner, a member of Eta Kappa Nu and Sigma Xi, and holds several patents. He was awarded an ONR Young Investigator Award and an NSF Research Initiation Award.