Project description
Artifical intelligence for high-capacity communication networks
The demands of high-speed, reliable and secure emerging internet, data centre, cloud computing, 5G and beyond systems have increased during the COVID-19 pandemic and require solutions for telecommunication networks with increased information capacity, intelligence and security. Artificial intelligence (AI) technologies have emerged as a promising solution for optical/wireless/hybrid networks. The EU-funded DIOR project will exploit a variety of the machine learning methods for efficient signal processing and resource allocation in optical/wireless/hybrid networks. The project will reduce signal distortions, predict network conditions and maximise network capacity. DIOR aims to integrate optical/radio network research and AI technologies and perform world-leading research on building a machine learning-underpinned communication platform to increase secure, intelligent and high-capacity communication networks.
Objective
Communication networks play a vital role in the technological infrastructure underpinning Internet traffic applications. Service providers and researchers worldwide are sparing no effort to increase the information capacity and security of telecommunication networks to support the demands of high-speed, reliable and secure emerging internet, data centre, cloud computing, 5G new radio and IoT systems, especially since the outbreak of Coronavirus. Applications such as intelligent transportation, signal processing ubiquitous low-latency connectivity and massive connected objects, have raised challenges for backbone and access networks that are often underpinned by optical, radio or hybrid networks. Artificial intelligent (AI) technologies appear an innovative and promising solution to cope with emerging challenges in optical/wireless/hybrid networks, in which the underlying physics, mathematics and optimisation of problems are non-deterministic to analyse or impossible to describe explicitly. In this proposed research, supervised, unsupervised and reinforcement learning techniques such as neural networks, clustering and regression will be exploited in optical/wireless/hybrid networks to mitigate stochastic distortions, to predict network conditions and to maximise network capacity. This DIOR proposal aims to unite optical/radio network research and AI technologies for tackling emerging challenges. This project aims to carry out world-leading research on building a machine learning-based communication platform to accelerate secure, intelligent and high-capacity communication networks.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences computer and information sciences internet internet of things
- engineering and technology electrical engineering, electronic engineering, information engineering information engineering telecommunications telecommunications networks optical networks
- medical and health sciences health sciences infectious diseases RNA viruses coronaviruses
- engineering and technology electrical engineering, electronic engineering, information engineering information engineering telecommunications radio technology
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions
MAIN PROGRAMME
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H2020-EU.1.3.3. - Stimulating innovation by means of cross-fertilisation of knowledge
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
MSCA-RISE - Marie Skłodowska-Curie Research and Innovation Staff Exchange (RISE)
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) H2020-MSCA-RISE-2020
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
33100 TAMPERE
Finland
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.