PROJECT TITLE: Complexity and bidirectional information theory: Complexity-Feedback-Performance limits and a new class of ecological information networks |
|PI||Petros ELIA (EURECOM, Sophia-Antipolis)|
|PROJECT TYPE||Jeune chercheuse - jeune chercheur|
|Type of research||Basic research|
|Duration||42 months (2015-2018)|
|Call targets||Défi 7: “Société de l’information et de la communication”|
|Axe||4 “Fondements du numérique”|
|ERC PANEL TARGETED||PE7: Systems and Communications Engineering|
KEYWORDS: statistical signal processing; detection and estimation; complexity theory of computation; information theory; interference; feedback; wireless information networks; power efficiency; ecological information networks.
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This project is in the context of wireless communications, and it aims to tackle 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.
Theoretical Vision: 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.
Novel Approach: We will take a novel approach, which drives our vision. A recent result of ours has revealed the surprising fact that – for a simple point-to-point setting – a single bit of feedback from the receiver back to the transmitter (properly placed in time, and properly representing the predicted flop count), managed to massively reduce the computational complexity of transceiver algorithms. This reduction was a surprising finding, and it was traced back to the newly-found ability of feedback to skew the statistics of the accumulation of computational load, without negatively skewing the statistics defining performance.
Naturally computational complexity, feedback and performance – are intertwined, and will be explored jointly. Finding the crucial and largely-unexplored complexity-feedback-performance interdependencies, will offer guiding principles for merging fog (decentralized) and cloud (centralized) ideas, towards hybrid solutions that better traverse the complexity-feedback-performance triangle by surgically inserting bidirectional bits and flops across the network nodes.