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 comprehensive survey on transfer learning
Transfer learning aims at improving the performance of target learners on target domains by
transferring the knowledge contained in different but related source domains. In this way, the …
transferring the knowledge contained in different but related source domains. In this way, the …
Federated transfer learning for authentication and privacy preservation using novel supportive twin delayed DDPG (S-TD3) algorithm for IIoT
S Maurya, S Joseph, A Asokan, AA Algethami… - Sensors, 2021 - mdpi.com
The Industrial Internet of Things (IIoT) has led to the growth and expansion of various new
opportunities in the new Industrial Transformation. There have been notable challenges …
opportunities in the new Industrial Transformation. There have been notable challenges …
Deep learning in mobile and wireless networking: A survey
The rapid uptake of mobile devices and the rising popularity of mobile applications and
services pose unprecedented demands on mobile and wireless networking infrastructure …
services pose unprecedented demands on mobile and wireless networking infrastructure …
Transfer learning promotes 6G wireless communications: Recent advances and future challenges
M Wang, Y Lin, Q Tian, G Si - IEEE Transactions on Reliability, 2021 - ieeexplore.ieee.org
In the coming 6G communications, network densification, high throughput, positioning
accuracy, energy efficiency, and many other key performance indicator requirements are …
accuracy, energy efficiency, and many other key performance indicator requirements are …
Application of machine learning in wireless networks: Key techniques and open issues
As a key technique for enabling artificial intelligence, machine learning (ML) is capable of
solving complex problems without explicit programming. Motivated by its successful …
solving complex problems without explicit programming. Motivated by its successful …
Intelligent resource slicing for eMBB and URLLC coexistence in 5G and beyond: A deep reinforcement learning based approach
In this paper, we study the resource slicing problem in a dynamic multiplexing scenario of
two distinct 5G services, namely Ultra-Reliable Low Latency Communications (URLLC) and …
two distinct 5G services, namely Ultra-Reliable Low Latency Communications (URLLC) and …
Machine learning for resource management in cellular and IoT networks: Potentials, current solutions, and open challenges
Internet-of-Things (IoT) refers to a massively heterogeneous network formed through smart
devices connected to the Internet. In the wake of disruptive IoT with a huge amount and …
devices connected to the Internet. In the wake of disruptive IoT with a huge amount and …
Intelligent 5G: When cellular networks meet artificial intelligence
5G cellular networks are assumed to be the key enabler and infrastructure provider in the
ICT industry, by offering a variety of services with diverse requirements. The standardization …
ICT industry, by offering a variety of services with diverse requirements. The standardization …
Energy-efficient base-stations sleep-mode techniques in green cellular networks: A survey
J Wu, Y Zhang, M Zukerman… - … surveys & tutorials, 2015 - ieeexplore.ieee.org
Due to global climate change as well as economic concern of network operators, energy
consumption of the infrastructure of cellular networks, or “Green Cellular Networking,” has …
consumption of the infrastructure of cellular networks, or “Green Cellular Networking,” has …