REAL-time monitoring and mitigation of nonlinear effects in optical NETworks (REAL-NET).
REAL-NET is a European Industrial Doctorate (EID) consortium.
REAL-NET is a doctoral-level training network funded by the European Commission under Horizon2020 Marie Skłodowska-Curie Actions (MSCA). The program will train 6 early-stage researchers (ESRs) in the area of machine learning algorithms for optical networks through collaboration of academic and industrial highly qualified institutions. In consists of:
REAL-NET has accomplished the recruitment process of six prestigious three years postgraduate positions as Early Stage Researcher (ESR) within the European Industrial Doctorate project REAL-NET. The project is supported through the Horizon 2020 Marie Skłodowska-Curieactions (MSCA).
For more information about the person specification and requirements of these positions please follow this link.
Within the exponential surge in the global data traffic, there is a clear need for development of radically different methods for coding, transmission, and (pre & post) processing of information to mitigate nonlinearities and to estimate important network parameters. The training of a new generation of engineers with expertise in optical communications, nonlinear science methods, digital signal processing (DSP), and design of implementable algorithms is of high importance.
From the industry perspectives, design of practical and implementable processing algorithms requires knowledge of ASICs and real-world conditions and restrictions. The multi-national & multi-interdisciplinary EID (European Industrial Doctorate) REAL-NET will provide timely doctoral training for 6 PhD students through industry relevant research (50% stay in industry) in a fast-growing area of high practical relevance. Solutions identified within REAL-NET will enable to overcome a possible traffic-crunch by achieving a manifold increase in the fibre-optic transmission speed.
More information on the project can be found here.
The specific Research (RO) and Training objectives (TO) of REAL-NET are:
RO1: To develop efficient, low complexity low-power-consumption algorithms suitable for real-time mitigation of nonlinear effects in optical fiber transmission, and to provide ESRs with corresponding skills required by industry.
RO2: To train ESRs to employ advanced machine learning signal processing schemes using the historical monitored data for real-time network monitoring and the design of the transmitter and receiver architectures.
RO3: To develop system designs based on the proposed algorithms and carry out an extensive experimental study of their performance in practical environments (in lab and field trial) providing ESRs with world-class expertise and skills required by telecommunication industry.
RO4: To develop techniques that can infer the impact of BER degradation on upper network layers and to develop planning algorithms that exploit them to improve the network performance and failure identification.
RO5: To ensure smooth transition of scientific innovation to industry through direct involvement of stakeholders in all elements of the chain from academic institutes and research centres to companies.
RO6: To ensure support of long-term, industry-oriented research through direct and close collaboration inside and outside of the REAL-NET consortium, during and beyond the lifetime of the proposed EID project;
TO1: General training objectives: (a) to provide opportunity to 6 ESRs to acquire unique multi-disciplinary knowledge and skills in the areas of high industrial relevance; (b) to advance the strength of the EU in producing top quality experts capable of creating a new generation of technology for future high-speed optical communications and nonlinear DSP; (c) to attain, through multi-national and intersector (academia/industry) training, the profile of a globally thinking, diverse, and innovative researcher/engineer with excellent communication and leadership skills;
TO2: Specific training objectives: (a) to acquire advanced multi-disciplinary knowledge at frontiers of communications engineering and nonlinear optics; (b) to obtain practical and hands-on skills in conducting experiments; (c) to improve employability chances for leading roles in the industry.