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Accordion: A Communication-Aware Machine Learning Framework for Next Generation Networks
Fadhel Ayed, Antonio De Domenico, Adrian Garcia-Rodriguez +1
In this article, we advocate for the design of ad hoc artificial intelligence (AI)/machine learning (ML) models to facilitate their usage in future smart infrastructures based on c…
Power Consumption Modeling of 5G Multi-Carrier Base Stations: A Machine Learning Approach
Nicola Piovesan, David Lopez-Perez, Antonio De Domenico +2
The fifth generation of the Radio Access Network (RAN) has brought new services, technologies, and paradigms with the corresponding societal benefits. However, the energy consumpti…
Machine Learning and Analytical Power Consumption Models for 5G Base Stations
Nicola Piovesan, David Lopez-Perez, Antonio De Domenico +3
The energy consumption of the fifth generation(5G) of mobile networks is one of the major concerns of the telecom industry. However, there is not currently an accurate and tractabl…
A Survey on 5G Radio Access Network Energy Efficiency: Massive MIMO, Lean Carrier Design, Sleep Modes, and Machine Learning
David Lopez-Perez, Antonio De Domenico, Nicola Piovesan +4
Cellular networks have changed the world we are living in, and the fifth generation (5G) of radio technology is expected to further revolutionise our everyday lives, by enabling a…
IEEE 802.11be: Wi-Fi 7 Strikes Back
Adrian Garcia-Rodriguez, David Lopez-Perez, Lorenzo Galati-Giordano +1
As hordes of data-hungry devices challenge its current capabilities, Wi-Fi strikes back with 802.11be, alias Wi-Fi 7. This brand-new amendment promises a (r)evolution of unlicensed…
Enabling AI in Future Wireless Networks: A Data Life Cycle Perspective
Dinh C. Nguyen, Peng Cheng, Ming Ding +6
Recent years have seen rapid deployment of mobile computing and Internet of Things (IoT) networks, which can be mostly attributed to the increasing communication and sensing capabi…