Séminaire général du département COMELEC

Christophe LOUSSERT, MOJIX, France

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.

Marco Di Renzo L2S, CentraleSupelec

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.