Summary
In the context of modern technologies, the transition to 6G networks faces numerous challenges; therefore, novel solutions must be discovered, combined, and tested in order to achieve distributed smart connectivity, imperceptible latency, virtually infinite capacity, improved security/privacy, smart/adaptive networking, and energy efficiency. The 6G-ICARUS project will investigate, combine, and improve on current technologies in order to address numerous obstacles that 6G networks will face in order to define the future wireless networks (FWNs).
6G-ICARUS is focused on FWNs capable of meeting a variety of targets, resulting in better geographic coverage, particularly in urban areas, higher transmission rates, lower latency, provision of diverse services, processing of information generated from a massive volume of heterogeneous sources, inherent resilience to counter potential security threats, and making intelligent decisions. 6G-ICARUS is founded on three pillars: (i) Effective utilisation of reconfigurable intelligent surfaces suitably controlled by artificial intelligence software; (ii) Channel modelling for mmWave/subTHz communications; (iii) Multi-connectivity solutions for 6G mobile communications.
The project will generate novel research results as well as novel original hardware supported by innovative software (techniques, algorithms) based mostly on machine learning and deep learning. Hardware and software will be combined and examined in real-world settings to fulfill certain situations, all of which are matched with real-world applications. There will be separate Proof of Concept studies to validate the technologies and methodologies under consideration.
6G-ICARUS is focused on FWNs capable of meeting a variety of targets, resulting in better geographic coverage, particularly in urban areas, higher transmission rates, lower latency, provision of diverse services, processing of information generated from a massive volume of heterogeneous sources, inherent resilience to counter potential security threats, and making intelligent decisions. 6G-ICARUS is founded on three pillars: (i) Effective utilisation of reconfigurable intelligent surfaces suitably controlled by artificial intelligence software; (ii) Channel modelling for mmWave/subTHz communications; (iii) Multi-connectivity solutions for 6G mobile communications.
The project will generate novel research results as well as novel original hardware supported by innovative software (techniques, algorithms) based mostly on machine learning and deep learning. Hardware and software will be combined and examined in real-world settings to fulfill certain situations, all of which are matched with real-world applications. There will be separate Proof of Concept studies to validate the technologies and methodologies under consideration.
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More information & hyperlinks
Web resources: | https://cordis.europa.eu/project/id/101131342 |
Start date: | 01-03-2024 |
End date: | 29-02-2028 |
Total budget - Public funding: | - 501 400,00 Euro |
Cordis data
Original description
In the context of modern technologies, the transition to 6G networks faces numerous challenges; therefore, novel solutions must be discovered, combined, and tested in order to achieve distributed smart connectivity, imperceptible latency, virtually infinite capacity, improved security/privacy, smart/adaptive networking, and energy efficiency. The 6G-ICARUS project will investigate, combine, and improve on current technologies in order to address numerous obstacles that 6G networks will face in order to define the future wireless networks (FWNs).6G-ICARUS is focused on FWNs capable of meeting a variety of targets, resulting in better geographic coverage, particularly in urban areas, higher transmission rates, lower latency, provision of diverse services, processing of information generated from a massive volume of heterogeneous sources, inherent resilience to counter potential security threats, and making intelligent decisions. 6G-ICARUS is founded on three pillars: (i) Effective utilisation of reconfigurable intelligent surfaces suitably controlled by artificial intelligence software; (ii) Channel modelling for mmWave/subTHz communications; (iii) Multi-connectivity solutions for 6G mobile communications.
The project will generate novel research results as well as novel original hardware supported by innovative software (techniques, algorithms) based mostly on machine learning and deep learning. Hardware and software will be combined and examined in real-world settings to fulfill certain situations, all of which are matched with real-world applications. There will be separate Proof of Concept studies to validate the technologies and methodologies under consideration.
Status
SIGNEDCall topic
HORIZON-MSCA-2022-SE-01-01Update Date
12-03-2024
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