PhD : Self-adaptive selection of radio access technologies to answer on-road communications needs for autonomous vehicle deployment
Description of the project, activities and work context
Communication needs for automotive applications will evolve and grow strongly with the arrival of Vehicular Ad-Hoc Network (VANET) and autonomous vehicles, which will enable the deployment of a wide variety of applications. While these new applications will focus on improving road safety and the comfort of users while traveling, new services will emerge such as platooning that will allow a vehicle with driver to guide autonomous vehicles assembled in a convoy on the urban network. The Internet of Things will further expand the scope of services offered. These applications, always more numerous, will have very different requirements in terms of quality of service (QoS) and security of the communications to which it will be necessary to answer. In particular, to become a reality on a daily basis, driving without a driver must be able to count on reliable means of communication at all times.
Radio access technologies that allow vehicles to communicate, either directly (V2V- Vehicle-to-Vehicle), or with a roadside communications infrastructure (V2I-Vehicle to Infrastructure), or directly with a network, are experiencing today considerable development with technologies such as ITS-G5 derived from Wi-Fi or Long Term Evolution (LTE). These developments will continue with the arrival of 5G NR, which should also standardize vehicle-to-vehicle (V2V) communications. Each of these technologies has particular characteristics such as bandwidth, radio range, availability and security, which are specific to it. Although specific bands are allocated for vehicular applications (ITS- Intelligent Transport System band), the coverage of a telecommunications network along roads and in low-density areas is far from complete because deployments are expensive. Cognitive radio (or Cognitive radio in English) is an emerging technology that will be able to detect unoccupied frequency bands and adapt its transmission parameters according to the constraints of communication in order to transmit in these bands. It will be able to use temporarily unused frequency bands in areas without communication infrastructure or in areas where radio traffic is low. In addition to being able to perceive and adapt itself to its environment, cognitive radio has reasoning and learning capabilities through the use of artificial intelligence technologies.
The aim of this thesis is to propose a solution that will allow the vehicle to select, in an autonomous way and in real time, the radio access technology (ies) that best meets the needs of road applications. In particular, it will be necessary to adapt the operation of cognitive radio so that it is able to select the best access technology (ies) in the presence of a certain number of constraints (quality of service, security, energy saving, etc.) and adjust the communication protocols and operational parameters accordingly. In addition, virtualization of network functions will facilitate the support of developments related to radio access technologies. The proposed solution will be validated by simulations and/or experimentations using a cognitive radio platform and considering different communication scenarios.
 S. Boussen, J. Arnaud, F. Krief, N. Tabbane, S. Tabbane; “IPTV QoS adaptation for multi-homed mobile terminals in a new IMS based architecture”. Telecommunication Systems 55(2): 199-210; 2014
 M. Peres, M. A. Chalouf, F. Krief; “A Run-Time Generic Decision Framework for Power and Performance Management on Mobile Devices”. UIC/ATC/ScalCom: 72-79; 2014
 K. D. Singh, P. Rawat and J-M. Bonnin; “Cognitive radio for vehicular ad hoc networks (CR-VANETs): approaches and challenges”, EURASIP Journal on Wireless Communications and Networking, 2014:49; 2014
 N. Haziza, M. Kassab, R. Knopp, J. Härri, F. Kaltenberger, P. Agostini, M. Berbineau, C. Gransart, J. Besnier, J. Ehrlich, H. Aniss, “Multi- technology vehicular cooperative system based on software defined radio (SDR)”, in proceedings, NET4CARS 2013, 5th International Workshop on Communication Technologies for Vehicles, May 14-15, 2013, Lille, France
 M. Berbineau & Al., “Cognitive Radio for High Speed Railway through Dynamic and Opportunistic spectrum Reuse”, in proceedings Transport Research Arena 2014, Paris
Skills (knowledge, know-how, know-how)
Curiosity, initiative, ability to listen and analyze, tenacity, team work, english
Machine Learning competences will be a plus.
Fluent French speaking Is mandatory
Degree required and / or level of qualification
Master degree or Engineering degree in computing science and networks
Location : Laboratoire Bordelais de Recherche en Informatique (LaBRI)
Type of contract : Temporary
Job status : full-time
Duration: 3 year
Starting Date : October/November 2019
Remuneration: 1900 € brut/month