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 5G/B5G mobile and wireless communications: Potential, limitations, and future directions
Driven by the demand to accommodate today's growing mobile traffic, 5G is designed to be
a key enabler and a leading infrastructure provider in the information and communication …
a key enabler and a leading infrastructure provider in the information and communication …
The role of artificial intelligence and machine learning in wireless networks security: Principle, practice and challenges
Security is one of the biggest challenges concerning networks and communications. The
problem becomes aggravated with the proliferation of wireless devices. Artificial Intelligence …
problem becomes aggravated with the proliferation of wireless devices. Artificial Intelligence …
Softwarization of UAV networks: A survey of applications and future trends
OS Oubbati, M Atiquzzaman, TA Ahanger… - IEEE Access, 2020 - ieeexplore.ieee.org
Unmanned Aerial Vehicles (UAVs) have become increasingly important in assisting 5G and
beyond 5G (B5G) mobile networks. Indeed, UAVs have all the potentials to both satisfy the …
beyond 5G (B5G) mobile networks. Indeed, UAVs have all the potentials to both satisfy the …
AFRL: Adaptive federated reinforcement learning for intelligent jamming defense in FANET
The flying ad-hoc network (FANET) is a decentralized communication network for the
unmanned aerial vehicles (UAVs). Because of the wireless nature and the unique network …
unmanned aerial vehicles (UAVs). Because of the wireless nature and the unique network …
6G-enabled network in box for internet of connected vehicles
Z Lv, L Qiao, I You - IEEE transactions on intelligent …, 2020 - ieeexplore.ieee.org
Objective: To realize the full coverage, full spectrum, and full application, of 6G networks, the
channel measurement, channel characteristics, and channel research of the 6G-oriented full …
channel measurement, channel characteristics, and channel research of the 6G-oriented full …
Generative adversarial network in the air: Deep adversarial learning for wireless signal spoofing
Y Shi, K Davaslioglu… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
The spoofing attack is critical to bypass physical-layer signal authentication. This paper
presents a deep learning-based spoofing attack to generate synthetic wireless signals that …
presents a deep learning-based spoofing attack to generate synthetic wireless signals that …
Survey on cognitive anti‐jamming communications
MA Aref, SK Jayaweera, E Yepez - IET Communications, 2020 - Wiley Online Library
In this study, the authors review various jamming and anti‐jamming strategies in the context
of cognitive radios (CRs). The study explores different jamming models and classifies them …
of cognitive radios (CRs). The study explores different jamming models and classifies them …
Reinforcement learning-based microgrid energy trading with a reduced power plant schedule
With dynamic renewable energy generation and power demand, microgrids (MGs)
exchange energy with each other to reduce their dependence on power plants. In this …
exchange energy with each other to reduce their dependence on power plants. In this …
Secure mobile edge computing networks in the presence of multiple eavesdroppers
In this paper, we investigate a secure mobile edge computing (MEC) network in the
presence of multiple eavesdroppers, where multiple users can offload parts of their tasks to …
presence of multiple eavesdroppers, where multiple users can offload parts of their tasks to …