An intelligent design of user-centric cell-free massive MIMO: A deep learning approach

Project Information

IUCCF

Grant agreement ID: 844253

DOI 10.3030/844253

Closed project

Start date 1 February 2020

End date 15 December 2022

Funded under

• EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions

Total cost € 183 473,28

EU contribution € 183 473,28

Coordinated by

UNIVERSITA DEGLI STUDI DI CASSINO E DEL LAZIO MERIDIONALE
Italy

Project description

Deep learning for next-generation intelligent wireless solutions

On the eve of 5G and the beyond-5G wireless networks, there are several problems that must be resolved. There is a need for ultra-high data rates to serve a huge number of devices. Ultra-reliable, low-latency communications and energy efficiency are also necessary. The EU-funded IUCCF project aims to design intelligent cellular wireless data networks by engaging a deep learning approach. The researcher will upgrade the traditional massive MIMO concept (sending and receiving multi-data signal over a radio channel with a multipath propagation) with antennas in the form of a simple access point (AP) as well as unmanned aerial vehicles (UAVs). The project will adopt machine learning tools, distributed optimisation and statistical signal processing.

Objective

IUCCF is a 24-months research project focusing on the intelligent design of future cellular wireless data networks. The project leverages on the concepts of ultra-dense network deployments, cloud-based implementations of radio access networks, and of cell-free, user-centric architecture. The aim is to be able to cope with the difficult challenges of future 5G and beyond-5G wireless networks, which will be required to provide ultra-high data-rates, to support a very large number of devices, to provide ultra-reliable and low-latency communications to specific applications, and to operate with the highest levels of energy efficiency. The project will explore the potentialities of the user-centric cell-free massive MIMO concept, where the antennas are distributed, in the form of simple access points (APs), in the service area instead of being collocated at a cell-center. In addition to the use of fixed APs (FAPs), as in traditional cell-free massive MIMO system, the project will introduce also moving APs in the form of unmanned aerial vehicles (UAVs). This scenario poses many issues related to network management and resource allocation schemes that should be considered.

During the project, the ER will learn and adopt tools from machine learning, distributed optimization and statistical signal processing to optimize and add intelligence at both network core and edge in order to tackle the challenges of such a distributed autonomous system.

The project will be carried out by the ER at the University of Cassino and Lazio Meridionale (Italy), under the supervision of Prof. Stefano Buzzi. Furthermore, Nokia Bell-Labs Research Center in Dublin (Ireland) will host the ER for a six-months secondment. The applying ER is Dr. Mohamed Elwekeil, currently a post-doctoral researcher at the college of information engineering, Shenzhen University, China.

Fields of science

• engineering and technology › electrical engineering, electronic engineering, information engineering › information engineering › telecommunications › telecommunications networks › mobile network › 5G
• engineering and technology › electrical engineering, electronic engineering, information engineering › electronic engineering › signal processing
• engineering and technology › electrical engineering, electronic engineering, information engineering › information engineering › telecommunications › telecommunications networks › data networks
• engineering and technology › electrical engineering, electronic engineering, information engineering › electronic engineering › robotics › autonomous robots › drones
• engineering and technology › electrical engineering, electronic engineering, information engineering › information engineering › telecommunications › radio technology

Keywords

• 5G and beyond-5G
• Mobile cellular networks
• Cell-free Massive MIMO
• Deep learning
• Machine learning for wireless communications
• Energy efficiency

Programme(s)

• H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions Main Programme
• H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility

Topic(s)

• MSCA-IF-2018 - Individual Fellowships

Call for proposal

H2020-MSCA-IF-2018

Funding Scheme

MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)

Coordinator

UNIVERSITA DEGLI STUDI DI CASSINO E DEL LAZIO MERIDIONALE

• Net EU contribution: € 183 473,28
• Address: Viale dell universita campus folcara ; 03043 Cassino ; Italy
• Region: Centro (IT) › Lazio › Frosinone
• Activity type: Higher or Secondary Education Establishments
• Other funding: € 0,00