Machine learning algorithms for energy efficient and QoS aware communications in heterogeneous 6G mmWave/sub-THz networks
Description of the granted funding
The rollouts of millimeter wave (mmWave, 28-100 GHz) band 5G New Radio technology is hampered by highly unreliable connectivity and poor energy efficiency severely violating the IMT-2020 requirements. Even though 5G systems are not yet fully deployed, 3GPP already starts standardization of 6G systems operating in sub-THz band (100-300 GHz) that will be subject to similar effects. In EFFICIENT we will develop models, methods, and practical algorithms simultaneously improving the energy efficiency and user performance at the radio access level in 5G/6G networks operating in mmWave and sub-Thz frequency bands. The successful completion of the project will speed up the rollout of mmWave 5G NR systems as well as standardization of future mmWave/sub-THz 6G systems as well as improve durability, energy efficiency, and recyclability of user equipment by increasing the battery lifetime.
Show moreStarting year
2023
End year
2025
Granted funding
Role in consortium of the Academy of Finland
Leader
Funder
Research Council of Finland
Funding instrument
Targeted Academy projects
Decision maker
Scientific Council for Natural Sciences and Engineering
15.11.2022
15.11.2022
Other information
Funding decision number
353126
Fields of science
Electronic, automation and communications engineering, electronics
Research fields
Tietoliikennetekniikka
Identified topics
5G, 6G, wireless networks, wireless communication