IEEE EUROCON 2017, 6 - 8 July 2017, Ohrid, Macedonia

Plenary Speakers


Wireless Communication Challenges in 5G towards Transforming Vertical Industries
Professor Petar Popovski, IEEE Fellow
Wireless Communications
Department of Electronic Systems
Aalborg University, Denmark

Outline:  While the previous generations of mobile communications were focused on providing high rates and seamless connectivity for the user, 5G is poised to change the vertical industries, such as energy, transport, industrial production, and health. There is a common consensus that 5G will consists of three different modes: extended Mobile Broadband (eMBB), Machine-Type Communication (mMTC) and Ultra-Reliable Low-Latency Communication (URLLC). With mMTC, the vertical industries get access to data from massive amount of sensors and unprecedented insights in e.g. energy infrastructure or supply chain. URLLC represents one of the most innovative features of 5G, enabling mission-critical communications, such as reliable remote action with robots or coordination among vehicles. The value brought by URLLC can be understood as follows: Once a vertical industry can safely assume that wireless connectivity is “truly anywhere and anytime” and can be guaranteed e.g.  >99.999% of the time, the approach to system design and operation changes fundamentally. This talk will introduce challenges faced by wireless communication on the path of creating 5G and transforming the current vertical industries into connected, fully digital verticals. It will present the fundamental tradeoffs that exist in designing the modes URLLC and mMTC, as well as architectures for supporting those services along with the extemelly high rates offerend by eMBB.



Nanotechnology Enabled Pathways for Energy Conversion
Professor Stephen Goodnick, IEEE Fellow

Department of Electrical Engineering
Ira A. Fulton School of Engineering  
Arizona State University, USA

Outline:  Nanostructured solar cells have multiple approaches by which they can improve photovoltaic performance through new physical approaches in order to reach thermodynamic limits of energy conversion, circumventing material limitations through bandgap engineered systems and providing new routes for low-cost fabrication by self-assembly or design of new materials. In the present talk, we focus on pathways to high efficiency solar cells and energy conversion using various approaches employing nanostructured materials. We first discuss the limits of conventional photovoltaics, and advanced concept approaches to exceed the so-called Shockley-Queisser limit for single bandgap cells. We then discuss particular approaches that are actively being investigated including Si heterojunction solar cells with carrier selective contacts, nanowire solar cells as active components of multi-junction solar cell, quantum dot solar cells for intermediate band devices, and multi-exciton generation for increasing the quantum yield above unity in quantum dot and nanowire structures.  Hot carrier solar cells are another approach to high efficiency discussed, where the critical issue is reducing the energy loss rate of photoexcited carriers, either in low-dimensional nanostructured materials where this rate is reduced, or in phononic bandgap materials in which nonequilibrium phonons reduce carrier cooling, and allow extraction at high energy.  Another way that nanomaterials improve efficiency which we discuss, is in improving light trapping of incident solar radiation, using nanowires and nanoparticles as scatterers in the diffraction limit, to increase absorption by increasing the optical path length in the device. Finally, we discuss hybrid high temperature multijunction photovoltaics coupled with concentrating solar thermal in order to improve the system efficiency above either that of the photovoltaic or CSP system by itself. 


Prof. dr. Rafael Mihalič

What does European Energy Turnover (Energiewende) Mean for Small countries
Professor Rafael Mihalič

Department of Power Systems and Devices Head
Laboratory of electric power and supply chief
University of Ljubljana, Slovenia

Outline: When talking about development of human society, it should be stressed that from the early beginnings its demographic, economic and social development has been crucially dependent on human ability to harvest the energy from available energy sources (literally life or death alternative). This ability and the availability of energy sources have determined the course of human history. Accessibility of energy sources which do not require too much society's activity in general (which could nowadays be expressed also as a share of GDP spent for energy, sometimes expressed as EROI – Energy Returned on Investment) is a precondition for the development of higher society's activities (like supporting inactive members, education, healthcare, art, etc.). In other words, in order to develop a successful society a reasonable tendency is to take advantage of those energy sources that exhibit a sufficiently large ERoEI (Energy Received on Energy Invested). With this respect, an example from the USA can be very illustrative. When nation's expenditure for primary energy, as a share of GDP, raises to about ten percent (historically up to fourteen percent), recessions tend to occur. On the other hand, during conjuncture the costs for primary energy is about 5% of the GDP.

Up to this moment, European Union (EU) has spent about 1000 billion Euros to support the political decision of realizing the so-called energy turnaround (known as Energievende). New political commitments at the EU level have been adopted to abandon the so-called carbon fuels, replacing them with the sustainable ones. As a result, questions like “what this actually means with respect to ERoEI of energy supply in general” and “how does this reflect to economies of individual countries involved” tend to appear. How much has the EU population contributed to sustainability of the energy supply by spending the already mentioned billions of Euros? Do we have enough wealth and/or resources to replace at least a considerable share of current electricity production with renewables? What does the extensive transition to renewables mean for countries' competitiveness on global market? Some authors dealing with the subject argue that the main dilemma is not about applying the renewable energy sources or not. Instead, either economic growth or sustainable society’s energy supply should be decided upon. Can the future of a country that decided for the sustainable alternative be foreseen if other countries do not follow the same pattern and consequently significantly overrun them in the economic sense? Does the society really gain by opening new jobs in the renewables industry while an individual coal-miner provides the society with 79 times more electricity as his colleague in the solar industry?

The presented dilemmas should be among the top few crucial questions of the modern society. It would be naive to expect final answers to raised questions from the lecture. On the other hand, it is of utmost importance to encourage discussions on the topic, especially following the latest attempts to criminalize the scepticism of catastrophic scenarios and to categorize any comments about mistrusting “world saving” activities as a hate speech. A primary aim of the lecture is therefore to open such a debate, where statements made base on series of firm and verifiable physical facts.


5G Mobile Networks: Implications for Operators, Verticals and End Users
Professor Eckhard Grass

Leader of Joint-Lab wireless broadband communication systems (IHP - HUB)
IHP - Leibniz-Institut für innovative Mikroelektronik
and Humboldt-Universität zu Berlin, Germany

Outline: Based on limitations and shortcomings of 4G, the main requirements for the 5th generation of mobile networks (5G) are outlined. The presentation highlights key architectural features, and target parameters of 5G. A summary of the key performance indicators (KPI) as targeted by the European 5G Infrastructure Public Private Partnership (5G-PPP) is given.

Furthermore, the main concepts for reaching the targeted key performance indicators (KPI) are outlined. This includes small cells, network virtualization, software defined networks (SDN), Cloud Radio Access Networks (C-RAN). Some concepts, specifically investigated by the 5G-XHaul project, are discussed. In particular, the application of different splits of Physical- and MAC-layer functionalities in the network, the concept of transport classes as well as techniques for supporting network slicing are outlined.

Moreover, technologies which are in the focus of current research, such as mmWave wireless systems, (massive-)MIMO and line-of-sight (LOS-)MIMO communications, passive and active fiber-optical systems and satellite links are highlighted. The potential of new modulation- and coding-schemes is briefly evaluated. For fiber optical communications, Time-Shared-Optical Networks (TSON) are a promising technology which will be briefly presented.

Based on the reviewed concepts and technologies, some important implications for Mobile Network Operators (MNO) and their future business models are outlined. Additionally, some implications for big companies (OEM or ‘verticals’) on their activities are derived. Finally the implications for the private end user are highlighted. In particular the performance, coverage, reliability and cost aspects will be elaborated on. Additionally, aspects such as security and privacy are visited.

The roadmap for the development, evaluation and commercial deployment of the 5G technology according to the 5G-PPP initiative is presented.

Further prospects of mobile communications systems, the required legal framework and future potential technologies will be highlighted.


Data Science profession and education 
Professor Yuri Demchenko,
System and Network Engineering Research Group
University of Amsterdam, Netherlands

I.     Introduction
Data Science is an emerging field of science, which requires a multi-disciplinary approach and has a strong link to Big Data and data driven technologies that create a strong transformational impact to all research and industry domains. Their sustainable development requires re-thinking and re-design of both traditional educational models and existing courses.

This talk will present a research and coordination activity done in the framework of the EU funded EDISON project to establish the new profession of Data Scientist for European research and industry [1, 2]. The EDISON project is specifically targeted to address issues of the data related skills and capacity building for European Open Science Cloud (EOSC) and European Digital Single Market (DSM), in particular targeting such issues as Data Stewardship, Research Data Management, research repeatability, and general data literacy.

The talk will provide overview of related research and activities to develop consistent and interoperable Data Science curricula that would empower the future graduates and professionals to build successful career paths as Data Scientist or other Data Science enabled professions. It will also refer to the Data Science champion universities community and related conference [3].

II.    Data Science Professional definition
There is no well established definition of the Data Scientist or Data Science profession due to a diverse number of competences and skills expected from these specialists. The EDISON project proposed the community endorsed definition based on the definition by the NIST SP1500-1 publication [4] and extended with the essential characteristic to deliver the value to the organisation: “A Data Scientist is a practitioner who has sufficient knowledge in the overlapping regimes of expertise in business needs, domain knowledge, analytical skills, and programming and systems engineering expertise to manage the end-to-end scientific method process through each stage in the big data lifecycle , till the delivery of expected scientific and business value to science or industry.”

The qualified Data Scientist should be capable of working in different roles in different projects and organisations such as Data Steward, Data Analyst, Data Architect, or Data Engineer, etc., and possess the necessary skills to effectively operate components of the complex data infrastructure and processing applications through all stages of the data lifecycle till the delivery of expected scientific and business values to science and/or industry.

III.   EDISON Data Science framework and Data Science Competences
The EDISON vision for building the Data Science profession will be enabled through the creation of a comprehensive framework for Data Science education and training that includes such components as Data Science Competence Framework (CF-DS), Data Science Body of Knowledge (DS-BoK) and Data Science Model Curriculum (MC-DS), Data Science Professional Profiles (DSPP) [5].

The CF-DS includes common competences required for successful work of Data Scientists in different work environments in industry and in research and through the whole career path.

  • Data Analytics including statistical methods, Machine Learning and Business Analytics
  • Data Science Engineering: software and infrastructure
  • Subject Domain competences and knowledge
  • Data Management, Curation, Preservation
  • Research Methods and Project Management

The DS-BoK defines the Knowledge Areas (KA) for building tailored Data Science curricula to support required Data Science competences. DS-BoK is organised by Knowledge Area Groups (KAG) that correspond to the CF-DS competence groups. DS-BoK incorporates best practices in Computer Science and domain specific BoK’s and includes KAs defined based on the Classification Computer Science (CCS2012), components taken from other BoKs and proposed new KAs to incorporate new technologies used in Data Science and their recent developments.

The MC-DS is built based on CF-DS and DS-BoK where Learning Outcomes are defined based on CF-DS competences and Learning Units are mapped to Knowledge Units in DS-BoK. Three mastery (or proficiency) levels are defined for each Learning Outcome to allow for flexible curricula development and profiling for different Data Science professional profiles.

IV.   Data Science design using EDSF
The EDSF can be used for designing customizable Data Science curricula for target group of students or learners. In practice, a new curriculum should be designed targeting a specific target group of learners that can described as target professional groups or professional profiles with the corresponding competence profiles as defined in DSPP. Competences are used to define the Learning Outcomes (LO) which map to the Knowledge Units (KU) of DS-BoK and Learning Units (LU) of MC-DS. The LU together with KU are used to advise the teacher or instructor on the content of the customized courses or programs. Decision will remain with the course developer who can use the advice to adopt to the specific groups or resources available.

The EDSF provides also effective tools for knowledge, competences and skills assessment as a part of education or certification process. It can be also used for Data Science team building and organizational skills management.


  1. EDISON Project: Building Data Science Profession [online]
  2. Yuri Demchenko, et al, EDISON Data Science Framework: A Foundation for Building Data Science Profession For Research and Industry, 3rd IEEE STC CC and RDA Workshop on Curricula and Teaching Methods in Cloud Computing, Big Data, and Data Science (DTW2016).
  3. Data Science champion universities community and conference [online]
  4. NIST SP 1500-1 NIST Big Data interoperability Framework (NBDIF): Volume 1: Definitions, Sept 2015 [online] nistpubs/SpecialPublications/NIST.SP.1500-1.pdf
  5. EDISON Data Science Framework [online]


 Josep Guerrero

Does DC Distribution Make Sense? 
Professor Josep M. Guerrero
Department of Energy Technology, Faculty of Engineering and Science
Aalborg University, Denmark


 Andrej Vckovski

Software Digital Waste Disposal 
Dr. Andrej Vckovski
President of the Swiss Internet Industry Association,
CEO and co-founder of  Netcetera,  Zürich, Switzerland

Outline: Current organizations in business and public administration are in a long-lasting process of digital transormation. New opportunities one the one side, a call for more efficiency and efficacy on the other side create an increasing demand for information systems in general. Every new system, however, generates additional system complexity if its operation does not dispose of legacy at the same time. Fields are not green anymore in most cases and therefore, the digital landscape of an organization already covered with many known and unknown elements of technology. This talk addresses awareness and strategy to cope with the increasing complexity within a system of systems based on practical examples of large-scale enterprise endeavours.