Doctorant sous la direction de S. LASAULCE

Titre de la thèse: Decision-oriented communication for electrical networks
Résumé de la thèse: The classic paradigm for designing a transmitter and a receiver is to design these elements by ensuring that the information reconstructed by the receiver is sufficiently close to the information that the transmitter has formatted to send it on the medium of communication; it is called fidelity criterion or reconstruction quality (measured for example in terms of distortion, bit error rate, packet error rate or communication cutoff probability). The problem of the classical paradigm is that it can lead to an unjustified investment in terms of communication resources (over-sizing of the data storage space, very high-speed and expensive communication medium, very fast components, etc.) and even making trade more vulnerable to attack. The reason for this is that exploiting the conventional approach (based on the criterion of information fidelity) in the electricity networks will typically lead to excessively rich information exchanges, which are too rich in terms of the decision to be made. the recipient of the information. It turns out that currently, the engineer does not have at his disposal a methodology to design such a transceiver pair that would be adapted to the use (or uses) of the recipient. The purpose of the proposed project is therefore to develop innovative coding and decoding techniques that take into account the use of decision-making devices in the transmission system.

Conference:

Decision-Oriented Communications: Application to Energy-Efficient Resource Allocation

H. Zou, C. Zhang, S. Lasaulce, L. Saludjian , and P. Panciatici

The 6th International Conference on Wireless Networks and Mobile Communications, 2018, Marrakesh, Morocco

 

Task Oriented Channel State Information Quantization

H. Zou, C. Zhang, and S. Lasaulce

IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, 2018, Bologna, Italy

 

Optimal Opponent Selection for Distributed Multi-Agent Self-Classification

Hang Zou, Youba Nait-Belaid, and Michel Kieffer

IEEE Global Communications Conference, 2018, Abu Dhabi, UAE

Journals: