Evolution of non-terrestrial networks from 5G to 6G: A survey
Non-terrestrial networks (NTNs) traditionally have certain limited applications. However, the
recent technological advancements and manufacturing cost reduction opened up myriad …
recent technological advancements and manufacturing cost reduction opened up myriad …
Machine learning in IoT security: Current solutions and future challenges
The future Internet of Things (IoT) will have a deep economical, commercial and social
impact on our lives. The participating nodes in IoT networks are usually resource …
impact on our lives. The participating nodes in IoT networks are usually resource …
Massive access for 5G and beyond
Massive access, also known as massive connectivity or massive machine-type
communication (mMTC), is one of the main use cases of the fifth-generation (5G) and …
communication (mMTC), is one of the main use cases of the fifth-generation (5G) and …
Future intelligent and secure vehicular network toward 6G: Machine-learning approaches
As a powerful tool, the vehicular network has been built to connect human communication
and transportation around the world for many years to come. However, with the rapid growth …
and transportation around the world for many years to come. However, with the rapid growth …
A survey of deep learning and its applications: a new paradigm to machine learning
Nowadays, deep learning is a current and a stimulating field of machine learning. Deep
learning is the most effective, supervised, time and cost efficient machine learning approach …
learning is the most effective, supervised, time and cost efficient machine learning approach …
Overview of deep learning-based CSI feedback in massive MIMO systems
Many performance gains achieved by massive multiple-input and multiple-output depend on
the accuracy of the downlink channel state information (CSI) at the transmitter (base station) …
the accuracy of the downlink channel state information (CSI) at the transmitter (base station) …
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 …
Data-driven deep learning for automatic modulation recognition in cognitive radios
Automatic modulation recognition (AMR) is an essential and challenging topic in the
development of the cognitive radio (CR), and it is a cornerstone of CR adaptive modulation …
development of the cognitive radio (CR), and it is a cornerstone of CR adaptive modulation …
Comprehensive survey on machine learning in vehicular network: Technology, applications and challenges
Towards future intelligent vehicular network, the machine learning as the promising artificial
intelligence tool is widely researched to intelligentize communication and networking …
intelligence tool is widely researched to intelligentize communication and networking …
Quantum machine learning for 6G communication networks: State-of-the-art and vision for the future
The upcoming fifth generation (5G) of wireless networks is expected to lay a foundation of
intelligent networks with the provision of some isolated artificial intelligence (AI) operations …
intelligent networks with the provision of some isolated artificial intelligence (AI) operations …