Energy Management and Protocol Design for Heterogeneous IoT Networks Leveraging Wake Up Radio

Defense type
Starting date
End date
IRISA Lannion
Main department

Mots clés: Wireless sensor network, Wake-up radio, IoT, Channel coding, MAC protocols


The Wake-up Radios (WuRs) are a new promising solution allowing asynchronous communications with  ultra low power consumption and low latency. WuR is however a matter of tradeoffs since to reduce as much energy consumption comes at the cost of low sensitivity and thus short range communications.   In this thesis, we propose to enhance the performances of the WuR by using an adequate channel coding. This channel coding is called minimum energy coding and allows to increase the sensitivity. We also propose an improved version of minimum energy coding for additional reduction in both energy consumption and latency. Improving the performance of only the device is not always  sufficient. As several devices are deployed in a network to form a wireless sensor network, it is important to pay attention to the design of the MAC protocol in order to obtain additional gains in range and energy consumption. We propose in this thesis a novel MAC protocol that allows long range communications while being energy efficient by combining WuR and LoRa. Another technique allowing to increase the range has been proposed by integrating the WuRs in a multi-hop network. Finally, devices resilience is limited when the devices are battery powered.  Energy harvesting, that converts energy from environmental sources, is a viable alternative to ensure sustainable operation and improve the quality of service of the network. We propose in this thesis an energy manager adapted to the heterogeneous architecture that combines WuR and LoRa.

Composition of the jury
Nathalie Mitton, Research Director, INRIA ( Reviewer)
Alain Pegatoquet, Associate Professor (HDR), Université Côte d’Azur (Reviewer)
Thomas Noel, Professor, Université de Strasbourg (Examiner)
Olivier Berder Professor, Université de Rennes 1 (PhD supervisor)
Matthieu Gautier Associate Professor (HDR), Université de Rennes 1 (PhD supervisor)
Antoine Courtay Associate Professor, Université de Rennes 1 ((PhD supervisor)
Fayçal Ait Aoudia Researcher, Nvidia (Guest)