6 month Internship with Railenium
5G waveforms based precoding and MIMO techniques for high data rate in uplink in the railway context
Location: Ifsttar F-59650 Villeneuve d’Ascq
Tutors: Marion Berbineau (Ifsttar), Iyad Dayoub (UVHC), Jean-Luc Perron (Thalès), Amine Didioui (SNCF I&R)
This internship is offered in a context of the TCRAIL project with SNCF and RAILENIUM which is a 42 months project that aims to develop two on site demonstrators for remote driving of a driverless train. This technological brick is mandatory for the development of full automatic driverless trains in a near future.
This internship will focus on the development of a bidirectional wireless communication system based on the future 5G technology for remote driving of a train from a control centre. For this particular application, the driver is not in the cabin of the engine but he is at the control centre with an appropriate human-machine interface. In this use case, the perception of the environment in front of the train should be transmitted in real time to the remote driver. The driver’s perception should be the same than the one in the cabin. Thus, the wireless link between the train and the ground (uplink) should be very high date rate, low latency, with a high QoS and the safety should be guaranteed. To develop such a system, there are several bottlenecks to solve such as:
– High data rate in uplink in railway environments
– Low latency, high QoS
– Availability and reliability of the system
In this internship we will focus on the uplink and on the Physical layer aspects for the development of suitable solutions that will contribute to the final solutions. 5G waveforms are based on multi-carriers and multi antennas technologies. We propose here to investigate the performance of precoding techniques associated to MIMO and beamforming in the railway environment.
The candidate will first investigate the last 5G waveforms proposed recently in the WONG5 project for critical communications (C-MTC). The characteristics of these waveforms will be identified and their performances will be investigated in the context of high speed railway channels with possible impulse noise. Then, taking into account the necessity for high data rate in uplink, it will be necessary to optimize MIMO techniques thus we propose to investigate suitable precoding techniques as a function of the number of antennas and the environment characteristics. A particular attention will be taken to the chosen channel model to evaluate the algorithms.
This internship is dedicated to candidates who are interested then to continue their studies with a doctoral position at Railenium in the framework of the project.
Missions: The work will start with a state of the art on 5G wave forms for critical communications, precoding and MIMO techniques that can operate with these waveforms, railway channels. The results of different European projects available in the project will be analysed. Some suitable techniques will be extracted. In parallel, the candidate will have to identify which type of channel model will be considered.
Thanks to simulations with Matlab, some of these techniques will be evaluated and compared in the context of railway and identification of the most suitable ones will be performed with simulations.
Solutions for the optimisation in the specific use case of remote driving will be proposed.
Skills: Wireless communications, signal processing, channel models, very good level of English, writing, knowledge of Railway domain will be a plus
Know-how: Autonomy, sense of initiative, Excellent relationship, rigor