AI models for green communications towards 6G
Green communications have always been a target for the information industry to alleviate
energy overhead and reduce fossil fuel usage. In the current 5G and future 6G eras, there is …
energy overhead and reduce fossil fuel usage. In the current 5G and future 6G eras, there is …
A tutorial on ultrareliable and low-latency communications in 6G: Integrating domain knowledge into deep learning
As one of the key communication scenarios in the fifth-generation and also the sixth-
generation (6G) mobile communication networks, ultrareliable and low-latency …
generation (6G) mobile communication networks, ultrareliable and low-latency …
Machine learning for 6G wireless networks: Carrying forward enhanced bandwidth, massive access, and ultrareliable/low-latency service
To satisfy the expected plethora of demanding services, the future generation of wireless
networks (6G) has been mandated as a revolutionary paradigm to carry forward the …
networks (6G) has been mandated as a revolutionary paradigm to carry forward the …
Wireless networks design in the era of deep learning: Model-based, AI-based, or both?
A Zappone, M Di Renzo… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
This paper deals with the use of emerging deep learning techniques in future wireless
communication networks. It will be shown that the data-driven approaches should not …
communication networks. It will be shown that the data-driven approaches should not …
Semi-distributed resource management in UAV-aided MEC systems: A multi-agent federated reinforcement learning approach
Recently, unmanned aerial vehicle (UAV)-enabled multi-access edge computing (MEC) has
been introduced as a promising edge paradigm for the future space-aerial-terrestrial …
been introduced as a promising edge paradigm for the future space-aerial-terrestrial …
Deep-learning-based wireless resource allocation with application to vehicular networks
It has been a long-held belief that judicious resource allocation is critical to mitigating
interference, improving network efficiency, and ultimately optimizing wireless communication …
interference, improving network efficiency, and ultimately optimizing wireless communication …
6G massive radio access networks: Key applications, requirements and challenges
Driven by the emerging use cases in massive access future networks, technological
advancements and evolutions are needed for wireless communications beyond the fifth …
advancements and evolutions are needed for wireless communications beyond the fifth …
Machine learning in beyond 5G/6G networks—State-of-the-art and future trends
Artificial Intelligence (AI) and especially Machine Learning (ML) can play a very important
role in realizing and optimizing 6G network applications. In this paper, we present a brief …
role in realizing and optimizing 6G network applications. In this paper, we present a brief …
Resource allocation for simultaneous wireless information and power transfer systems: A tutorial overview
Over the last decade, simultaneous wireless information and power transfer (SWIPT) has
become a practical and promising solution for connecting and recharging battery-limited …
become a practical and promising solution for connecting and recharging battery-limited …
Cooperative train control during the power supply shortage in metro system: A multi-agent reinforcement learning approach
X Wang, A D'Ariano, S Su, T Tang - Transportation Research Part B …, 2023 - Elsevier
In metro system, the fault of traction power supply system may cause the power supply
shortage around the failure substation. In this case, the dispatching measure should be …
shortage around the failure substation. In this case, the dispatching measure should be …