Project description
Designing the next generation of high-capacity optical networks
Six early-stage researchers are to be trained in machine learning (ML) applications in multiband optical communications. This is an interdisciplinary field of high industrial importance. The EU-funded MENTOR project has defined the research and training topics to be studied, and secured partnerships with four large companies. The aim of the project is to design the next generation of high-capacity optical networks, which are a key enabler of the global telecommunication infrastructure. Increasing demand (+ 20 % per year) requires a boost in capacity, and calls for operators to reduce the cost per transmitted bit. The search for a solution is leading researchers in the direction of ML techniques. In fact, ML is the technique of choice to tackle this kind of complex technical problem.
Objective
Optical fiber networks is one of the major drivers of our societal progress and a key enabler of the global telecommunication infrastructure. Optical networks underwent considerable changes over the past decade, as consequence of a continuous growth (exceeding 20% per year) of bandwidth demand. The current growth sets strong requirements in terms of capacity and costs for the operators, which seek to decrease the cost per transmitted bit. Several solutions have been proposed, and among them wide-band is more favourable to network operators, compared to more/or novel fibers. However, wide-band optical system presents new major challenges: optical components must guarantee similar performance over a broad spectrum, network optimization is carried out on a non-flat spectrum and with a much larger number of channels making design, optimization and control a complex problem. Therefore, application of machine learning (ML) techniques is of the growing importance for high-capacity multi-band (MB) optical systems. ML is becoming the technique of choice to solve complex nonlinear technical problems, such as, advance component design and management of wide-band networks.
The European Industrial Doctorate MENTOR presents a timely proposal to train 6 ESRs in the interdisciplinary field of high industrial importance: ML applications in multi-band optical communications. As ML can properly works only when a large amount of real data is available, it is crucial to bring together academic partners and the industry that provide access to the data. MENTOR consortium offers the strong industrial commitment of four large companies (CORIANT Germany and Portugal, ORANGE Labs and TELECOM ITALIA MOBILE) that significantly contributed in defining the research and training topics to be studied together with the world-leading academic partners in MENTOR. MENTOR will contribute to the European economy by design of the next generation of high-capacity optical 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.
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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.1.3.1. - Fostering new skills by means of excellent initial training of researchers
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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-ITN - Marie Skłodowska-Curie Innovative Training Networks (ITN)
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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-ITN-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.
B4 7ET Birmingham
United Kingdom
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.