An intelligent design of user-centric cell-free massive MIMO: A deep learning approach
Sector: Broadband • Location: Italy
Source: EU Funding & Tenders Portal
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
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Participants
Sponsoring Agency | Obfuscated Data |
Company | Obfuscated Data |
Status
Original status | ended |
Taiyo status | Obfuscated Data |
Taiyo last update | 00-00-0000 |
Available timestamps | 00-00-0000 |
Available timestamp type | Obfuscated Data |
Contact
Contact name | Obfuscated Data |
Phone | 0000000000 |
ObfuscatedData@email.com | |
Address | Obfuscated Data, Obfuscated data, obfuscated data, Obfuscated data |
Description
Description | 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. |
Original sub-sector | Obfuscated |
Original Currency | USD |
Original budget | 000000000000000 |
Procurement method | Obfuscated Data |
Budget | 000000000000000 |
Location
Region | Obfuscated |
Country | Obfuscated |
State | Obfuscated Data |
County | Obfuscated |
Location | Obfuscated Data, Obfuscated data, obfuscated data, Obfuscated data |
Source
Source reliability | High |
Data quality score | 100% |
Source | Obfuscated Data |
URL | obfuscated_data,obfuscateddata.com |
More Details
Project Type | Obfuscated Data |
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