The Internet of Things is a major technical and economic challenge for 5G: up to 50 billion objects are expected to be connected, mainly via wireless links.
Various technological solutions are being developed and deployed (e.g. based on the IEEE 802.15.4 standard), particularly in the 2.4 GHz ISM band, and, more recently, low-power, long-distance technologies such as LoRa or SigFox. Whatever the application and radio solution, connections must be reliable à at low power. In particular the interferences of different origins (internal to the network or coming from other networks) are a factor that significantly limits system performance. Our research focuses on this type of environment, with two major problems
- The low consumption by including all the consumption necessary for a communication, hardware and software.
- The Reliability in an environment that can present strong variations due to the radio channel and interference.
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Contact: Laurent Clavier
Interference modeling
The first observation is that the hypothesis of Gaussian noise is not verified. Models that take account of the dynamic and impulsive nature of the noise are needed. We are essentially working on alpha-stable models. The second point is to model the dependency structure in this type of model. Correlation is not suitable and we propose to use copulas.
Measurement of power consumption and interference
When the noise is not Gaussian, the linear receivers normally used are no longer suitable. Maximum likelihood requires the introduction of non-linearities which can be prohibitive in terms of computation time. We propose reduced-complexity solutions that are robust regardless of the nature of the interference.
Two aspects are studied:
- Capacity of an alpha-stable additive noise channel
- Receiver design
Impact of this interference on the communication chain
The CSAM group has developed a platform for measuring the power consumption of the various components of an object. This enables us to carry out a detailed analysis of the impact of interference on power consumption, taking into account the entire communication protocol - the physical and network layers - as well as the power consumption of the microcontroller. In particular, these measurements enable us to develop MAC layers that are adapted to the highly changeable environment that objects can encounter.
Neuromorphic technologies offer processing capabilities combined with improved energy efficiency, which is crucial for the IoT .
This area is based on a bioinspired approach to information processing and transmission system architectures. In close partnership with the ANODE group, the CSAM group has developed expertise in the modelling, design and experimental validation of an ultra-low-energy consumption neuromorphic spike technology for embedded A.I. based on the Edge Computing concept. This technology is currently the subject of a cluster of 7 patents and can be adapted to different modalities (vision, acoustic waves, electromagnetic waves) by means of neural spike encoders capable of addressing physical quantities (luminance, sound intensity, electromagnetic power) but also metrics (e.g. difference in arrival time) with energy consumption down to a few picoWatts.
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Contact: Christophe Loyez
Wake-up receiver
Bioinspired receptor using CMOS technology
The CSAM group is developing a new generation of bioinspired receivers capable of constantly monitoring the radio channel to identify a specific electromagnetic signature, with energy consumption of just a few dozen nanoWatts. This patented technology is involved in several of the group's projects (SATT-Nord Maturation, ANR). One major application concerns radio wake-up devices that can be used to wake up an IoT node in a dense network of connected objects.
Reference :
Patent "Signal Detector"WO2023031324 (A1) (Collaboration with the ANODE group)
Bioinspired localisation devices
Example of an integrated location system
Using a transmodal approach, a coincidence detector has been implemented to provide a high-performance sound source position indicator. This detector can be used to map the surrounding space in 2D and 3D, taking its inspiration from the mechanisms of auditory localisation. This device is at the heart of several projects, including the ANR ULP smart Cochlea project on monitoring underwater biodiversity.
Reference :
Patent "Coincidence Detector for locating a source"WO2023099355 (A1)
Collaboration with the ANODE and COMNUM groups
Bioinspired sensors for the intelligent city
The CAM group has encouraged the creation of a joint team (e-COST: Enhanced Communication devices for Smart cities and Transports) IEMN - Gustave Eiffel. This team was formalised in January 2020 to bring together resources and staff working on common research themes related to smart cities and transport. In particular, this framework will enable the technologies developed by the group to be evaluated in a representative environment through the Living Lab concept.
Link to the website Gustave Eiffel University
