Applications of deep reinforcement learning in communications and networking: A survey
This paper presents a comprehensive literature review on applications of deep
reinforcement learning (DRL) in communications and networking. Modern networks, eg …
reinforcement learning (DRL) in communications and networking. Modern networks, eg …
Deep reinforcement learning for Internet of Things: A comprehensive survey
The incumbent Internet of Things suffers from poor scalability and elasticity exhibiting in
communication, computing, caching and control (4Cs) problems. The recent advances in …
communication, computing, caching and control (4Cs) problems. The recent advances in …
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 …
Big data analytics for 6G-enabled massive internet of things
Z Lv, R Lou, J Li, AK Singh… - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
The purposes are to enable large-scale Internet of Things (IoT) devices to analyze data
more effectively and provide high-efficiency, low-energy, and wide-coverage technical …
more effectively and provide high-efficiency, low-energy, and wide-coverage technical …
A gentle introduction to reinforcement learning and its application in different fields
Due to the recent progress in Deep Neural Networks, Reinforcement Learning (RL) has
become one of the most important and useful technology. It is a learning method where a …
become one of the most important and useful technology. It is a learning method where a …
Reinforcement learning-based physical cross-layer security and privacy in 6G
Sixth-generation (6G) cellular systems will have an inherent vulnerability to physical (PHY)-
layer attacks and privacy leakage, due to the large-scale heterogeneous networks with …
layer attacks and privacy leakage, due to the large-scale heterogeneous networks with …
DeepEDN: A deep-learning-based image encryption and decryption network for internet of medical things
Internet of Medical Things (IoMT) can connect many medical imaging equipment to the
medical information network to facilitate the process of diagnosing and treating doctors. As …
medical information network to facilitate the process of diagnosing and treating doctors. As …
Security threats and artificial intelligence based countermeasures for internet of things networks: a comprehensive survey
The Internet of Things (IoT) has emerged as a technology capable of connecting
heterogeneous nodes/objects, such as people, devices, infrastructure, and makes our daily …
heterogeneous nodes/objects, such as people, devices, infrastructure, and makes our daily …
No Radio Left Behind: Radio Fingerprinting Through Deep Learning of Physical-Layer Hardware Impairments
K Sankhe, M Belgiovine, F Zhou… - IEEE Transactions …, 2019 - ieeexplore.ieee.org
Due to the unprecedented scale of the Internet of Things, designing scalable, accurate,
energy-efficient and tamper-proof authentication mechanisms has now become more …
energy-efficient and tamper-proof authentication mechanisms has now become more …
A systematic review on Deep Learning approaches for IoT security
The constant spread of smart devices in many aspects of our daily life goes hand in hand
with the ever-increasing demand for appropriate mechanisms to ensure they are resistant …
with the ever-increasing demand for appropriate mechanisms to ensure they are resistant …