Description
Date depot: 1 janvier 1900
Titre: Using predictions to reduce complexity and feedback in wireless communications
Directeur de thèse:
Petros ELIA (Eurecom)
Domaine scientifique: Sciences et technologies de l'information et de la communication
Thématique CNRS : Non defini
Resumé:
Wireless communications are currently exhibiting a giant leap in volume and societal impact, but are also facing a massive environmental challenge in the form of a carbon footprint that matches that of global aviation, and which will triple by 2020. This challenge has spurred worldwide research to produce radically new power-efficient high-performance environmentally-friendly communication technologies. However, the efforts have encountered two seemingly insurmountable bottlenecks; the bottleneck of computational complexity corresponding to the need for algorithms that require extreme computing resources, and the bottleneck of feedback corresponding to the need for equally idealistic feedback mechanisms that must disseminate massive amounts of overhead information about the fluctuating states of each link in the network.
These bottlenecks drive our theoretical vision: We will provide a never-before-attempted exploration of the crucial interdependencies between computational complexity, feedback and performance in wireless communications. They also drive our technological vision: We will develop algorithms for a new class of mobile-user devices that can participate in properly gathering/disseminating feedback (at the right place and time) as well as in computing solutions to outsourced algorithmic tasks across the network, in an effort which we term as “outsourcing the surgical insertion of bidirectional bits and flops across the network” and which aims to reduce computational complexity and improve performance.
Doctorant.e: Lampiris Eleftherios