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Professor Nicola Marchetti

Associate Professor (Electronic & Elect. Engineering)
      
Profile Photo

Professor Nicola Marchetti

Associate Professor (Electronic & Elect. Engineering)

 marchetn@tcd.ie

 


Dr. Nicola Marchetti is Professor in Wireless Communications at Trinity College Dublin, Ireland. He is an IEEE Senior Member, a Fellow of Trinity College, and was an IEEE Communications Society Distinguished Lecturer. He received the PhD in Wireless Communications from Aalborg University, Denmark in 2007, the MSc in Electronic Engineering from University of Ferrara, Italy in 2003, and the MSc in Mathematics from Aalborg University in 2010. He has authored more than 190 journals and conference papers, 2 books and 9 book chapters, holds 4 patents, and received 4 best paper awards. His research interests span Complex Networks, Mathematics for Communications & Computing, Network Resource Allocation, and Signal Processing for Communications. He serves as Technical Editor for IEEE Wireless Communications, and has served as an Associate Editor for IEEE Network, the IEEE Internet of Things Journal and the EURASIP Journal on Wireless Communications and Networking. He has an extensive experience giving research lectures across the globe, having delivered to date 4 keynotes, 9 IEEE ComSoc distinguished lectures, 20 invited talks, 8 tutorials at international conferences, and 8 international PhD courses.
  Wireless Communication   Wireless Networks
Project Title
 COALESCE (Joint Optimization of Data and Energy Networks for digitizing Sustainable Communities)
From
2023
To
2027
Summary
Funding Agency
European Commission
Programme
Marie Sklodowska-Curie Action
Project Type
Staff Exchanges
Project Title
 Digitising Biodiversity: Landscape-Animal-Digital-Human Translations
From
2021
To
2026
Summary
This project aims to develop a smart environmental monitoring system that will bring about a revolution in biodiversity quantification in real time. It will address the connected challenge of addressing explicitly what is lost and gained through digital translation from animal to human understanding.
Funding Agency
Trinity College Dublin
Programme
Kinsella Challenge-Based E3 Multi-Disciplinary Project Award
Project Title
 PlastG (Fungibility in Mobile networks for Resilient 6G)
From
To
Summary
Funding Agency
Research Ireland
Programme
US-Ireland R&D Partnership Programme
Project Title
 FIREMAN (Framework for the Identification of Rare Events via MAchine learning and IoT Networks)
From
2019
To
2023
Summary
The Internet of Things (IoT) is creating a new structure of awareness - a cybernetic one - upon physical processes. Industries of different kinds are expected to join soon this revolution, leading to the so-called Factories of the Future or Industry 4.0. Our considered IoT-based industrial cyber-physical system (CPS) works in three generic steps: 1) Large data acquisition / dissemination: A physical process is monitored by sensors that pre-process the (assumed large) collected data and send the processed information to an intelligent node (e.g. aggregator, central controller); 2) Big data fusion: The intelligent node uses machine learning techniques (e.g. data clustering, pattern recognition, neural networks) to convert the received ("big") data to useful information to guide short-term operational decisions related to the physical process; 3) Big data analytics: The physical process together with the acquisition and fusion steps can be virtualized, building then a cyber-physical process, whose dynamic performance can be analysed and optimized through visualization (if human intervention is available) or artificial intelligence (if the decisions are automatic) or a combination thereof.
Funding Agency
Irish Research Council
Programme
Future and Emerging Technologies (FET), EC ERA-NET
Project Title
 Addressing the future wireless network capacity scaling trough massive MIMO and millimetre Wave technologies and a user centric networking
From
2017
To
2021
Summary
The fifth generation (5G) wireless communication network is expected to connect everything and everyone, including the traditional human-to-human communications but also those between autonomous smart entities, like buildings, vehicles and sensors. Applying previous practical experience at Nokia Bell Labs in the design and implementation of cutting edge 5G massive MIMO prototypes, the aim of this PhD is to further develop and enhance the performance of 5G networks. One of the main challenges of this project is to deal with the 5G traffic heterogeneity, i.e., delivering a larger capacity for broadband services (e.g. virtual reality), while providing reliable services to a multitude of Internet of Things (IoT) devices. To address this challenge, the focus will be on a new 5G heterogeneous network comprised of two disruptive technologies, massive multiple-input multiple-output and millimetre-wave, proposing novel theoretical analysis tools and machine learning algorithms to realize an efficient integration of both technologies into the new network and providing an efficient radio resource management able to deal with network dynamics. A novel theoretical framework is needed to understand the performance of thousands of new 5G base stations communicating with millions of users, and gain key insights to develop tailored algorithms. Machine learning will be the basis of such algorithms, allowing for the first time to leverage the vast amount of information that millions of nodes can produce at the physical and medium access control layers. The outcome of this project will be novel analysis tools and algorithms that allow an efficient 5G operation, enhancing the network capacity by a factor of 100x as compared to current deployments, as well as the publication of research articles, patents and standardization contributions that will help define the technology advantage of Nokia Bell Labs and enhance the scientific contribution of the Irish ecosystem to the new communication era.
Funding Agency
Irish Research Council
Programme
Irish Research Council Enterprise Partnership Scheme 2016

Page 1 of 3
Details Date From Date To
IEEE 01 January 2013
D. Gutierrez-Rojas, C. Kalalas, I. Christou, G. Almeida, E. Eldeeb, S. Bakri, N. Marchetti, J. Sant"Ana, O. Alcaraz Lopez, H. Alves, C. Papadias, M. Haroon Tariq, P. Nardelli, Detection and Classification of Anomalies in WSN-enabled Cyber-physical Systems, IEEE Sensors Journal, 2025, Journal Article, PUBLISHED  DOI
I. Dey, N. Marchetti, Quantum Teleportation in Higher Dimension and Entanglement Distribution via Quantum Switches, IET Quantum Communication, 2025, Journal Article, PUBLISHED  DOI
Zandamela, A. and Marchetti, N. and Narbudowicz, A., Low-Profile Electrically Small Antenna with Pattern and Polarization Diversity, 2024, Notes: [cited By 1], Conference Paper, PUBLISHED  DOI
Antony, L. and Zandamela, A. and Marchetti, N. and Narbudowicz, A., Angle of Arrival Estimation Methods Using Spherical-Modes-Driven Multiport Antennas, 2024, Notes: [cited By 0], Conference Paper, PUBLISHED  DOI
Zandamela, A. and Marchetti, N. and Narbudowicz, A., Bandwidth-Enhanced Compact Beamsteering Antenna for IoT Platforms, 2024, Notes: [cited By 0], Conference Paper, PUBLISHED  DOI
A. Kalavampara Raghunadhan, M.G. De Andrade, D. Towsley, I. Dey, D. Kilper, N. Marchetti, Optimal Monitor Placement in Quantum Network Tomography, IEEE International Conference on Quantum Computing & Engineering (QCE), 2024, Conference Paper, PUBLISHED  DOI
I. Dey, N. Marchetti, M. Caleffi, A.S. Cacciapuoti, Quantum Game Theory meets Quantum Networks, IEEE Wireless Communications, 31, (4), 2024, p90-96 , Journal Article, PUBLISHED  DOI
L. Antony, A. Zandamela, N. Marchetti, A. Narbudowicz, Virtual Spherical Modes for AoA Estimation with Small Sub-Wavelength Antennas, IEEE Antennas and Wireless Propagation Letters, 2024, Journal Article, PUBLISHED  DOI
Abel Zandamela, Nicola Marchetti, Adam Narbudowicz, Directional Modulation for Enhanced Privacy in Smartwatch Devices: Proposing a security solution compatible with Internet of Things devices, IEEE Antennas & Propagation Magazine, 66, (2), 2024, p59-69 , Journal Article, ACCEPTED  TARA - Full Text  DOI
Abel Zandamela, Nicola Marchetti, Max J Ammann, and Adam Narbudowicz, 3-D Beam-Steering MIMO Antenna for On-Body IoT Applications, IEEE Transactions on Antennas and Propagation, 72, (3), 2024, p2241 - 2251 , Journal Article, PUBLISHED  TARA - Full Text  DOI
  

Page 1 of 22
Artificial intelligence-aided resource sharing for wireless mesh networks in, editor(s)L. Davoli, G. Ferrari , Wireless Mesh Networks for IoT and Smart Cities: Technologies and applications, IET, 2022, [I. Dey, G. Ropokis, N. Marchetti], Book Chapter, PUBLISHED
N. Marchetti, I. Dey, ENTROPY: Flexible and Autonomous Topology-based Networking Framework, European Autonomous Network Forum, Dublin, 28-09-2022, 2022, Huawei, Invited Talk, PUBLISHED
Nicola Marchetti, Communication, Computing and Network Automation: How can Complex Systems Science and AI help?, SRE Summit Conference 'Running Planet Scale Systems', 2020, Huawei, Invited Talk, PUBLISHED
Special Issue "Complex Networks Analysis and Engineering in 5G and beyond towards 6G", IEEE Access, (2020), 227751 - 227755p, M. Butt, C. Grebogi, I. Macaluso, M. Baptista, N. Marchetti, P. Juliano Nardelli, R. Hunjet, R. Thomas, [Guest Editor], Journal, PUBLISHED
Caching at the Edge in Low Latency Wireless Networks in, editor(s)Muhammad Ali Imran, Qammer H. Abbasi, Sajid Hussain , Wireless Automation as an Enabler for the Next Industrial Revolution, Wiley, 2019, [R. Amer, M. Butt, N. Marchetti], Book Chapter, PUBLISHED
A. Chiumento, N. Marchetti, I. Macaluso, Energy Efficient WSN: a Cross-layer Graph Signal Processing Solution to Information Redundancy, International Symposium on Wireless Communication Systems (ISWCS), 2019, Conference Paper, PUBLISHED
Nardelli, C. Papadias, C. Kalalas, H. Alves, I. Christou, I. Macaluso, N. Marchetti, R. Palacios, J. Alonso-Zarate, Framework for the Identification of Rare Events via Machine Learning and IoT Networks, International Symposium on Wireless Communication Systems (ISWCS), 2019, Conference Paper, PUBLISHED
Nicola Marchetti, Principles and Practice of Self-Organization in 6G Networks, International Conference on Information, Communication and Automation Technologies (ICAT), Sarajevo, 2019, University of Sarajevo, Invited Talk, PRESENTED
Spectrum Sharing between Radar and Small Cells in, Radar and Communication Spectrum Sharing, 2018, [F. Paisana, J. Rezende, L. DaSilva, N. Marchetti], Book Chapter, PUBLISHED
Nicola Marchetti, Performance Limits of Ultra Dense and millimetre-Wave 5G Networks, Glasgow, UK, 2018, University of Glasgow, Invited Talk, PRESENTED

  


Page 1 of 6
Award Date
IEEE ComSoc Distinguished Lecturer 2023-2024
Fellow of Trinity College Dublin 2022
ERC CoG interview stage 2019
Best Paper Award, IEEE International Conference on Communications (ICC) May 2016
IEEE Senior Member July 2015
Best Paper Award, International Symposium on Wireless Personal Multimedia Communications (WPMC) Oct 2010
Best Paper Award, Communications International Conference (COMM) Jun 2010
Best Paper Award, European Wireless Conference (EW) May 2009
I am an expert in the domain of digital signal processing and resource allocation for wireless communication, and am pioneering the application of complex systems science to communication networks. My research develops vital technology components essential to push beyond the boundaries of current communication networks, to cope with the current surge in mobile data demand, in a way that is both economical and sustainable. This can be achieved by distributing the intelligence within the network among many distributed simpler entities while "stretching" the dimensionality of important factors at play, i.e. increasing (i) the radio transmitter deployment density; (ii) the infrastructure dynamics (such as when considering drones as communicating entities); (iii) the radio frequency carrier and bandwidth. As an important complement to the above strategy, I am very interested in studying the implication of the topology of physical and functional interactions within wireless networks in achieving global desired network performance while acting locally based on simple interacting devices.