A review of the state of the art and future challenges of deep learning-based beamforming

H Al Kassir, ZD Zaharis, PI Lazaridis… - IEEE …, 2022 - ieeexplore.ieee.org
The key objective of this paper is to explore the recent state-of-the-art artificial intelligence
(AI) applications on the broad field of beamforming. Hence, a multitude of AI-oriented …

Feature extraction based on hierarchical improved envelope spectrum entropy for rolling bearing fault diagnosis

Z Chen, Y Yang, C He, Y Liu, X Liu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Bearing is the key part of mechanical equipment, which can support the rotating machinery
running. It is crucial to diagnose bearing faults in time to ensure mechanical equipment …

Machine-learning techniques can enhance dairy cow estrus detection using location and acceleration data

J Wang, M Bell, X Liu, G Liu - Animals, 2020 - mdpi.com
Simple Summary We investigated the feasibility of combing location, acceleration, and
machine learning technologies to accurately detect dairy cows in estrus. An automatic data …

Secrecy energy efficiency maximization for distributed intelligent-reflecting-surface-assisted MISO secure communications

H Song, H Wen, J Tang, PH Ho… - IEEE Internet of Things …, 2022 - ieeexplore.ieee.org
This article investigates energy-efficient secure communication design with the help of
multiple phase-adjustable intelligent reflecting surfaces (IRSs). By creating desirable …

Securing multiuser underlay cognitive transmissions with hardware impairments and channel estimation errors

P Yan, X Ji, Y Zou, B Li - IEEE Transactions on Cognitive …, 2023 - ieeexplore.ieee.org
We investigate physical-layer security for a multiuser underlay cognitive system with
hardware impairments (HIs) and channel estimation errors (CEEs), which comprises …

Multi-time scale optimal dispatch for the wind power integrated system with demand response of data centers based on neural network-based model predictive control

O Han, T Ding, C Mu, Y Huang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Data centers (DCs) are energy consumers with high electricity demand. Due to their Spatio-
temporal demand response (DR) capabilities, DCs are crucial DR participants. In view of the …

A hybrid forecasting model for the velocity of hybrid robotic fish based on back-propagation neural network with genetic algorithm optimization

X Shen, Y Zheng, R Zhang - IEEE Access, 2020 - ieeexplore.ieee.org
Marine unmanned vehicle is a novel robot widely used in ocean observation, and its
accurate control is of significance to their path planning. We want to find a method to predict …

On the security–reliability and secrecy throughput of random mobile user in Internet of Things

J Tang, H Wen, H Song, T Zhang… - IEEE Internet of Things …, 2020 - ieeexplore.ieee.org
Physical-layer security (PLS) in Internet of Things (IoT) has attracted great attentions
recently. Although mobility is an intrinsic property of IoT networks, most of the existing works …

Physical layer secure MIMO communications against eavesdroppers with arbitrary number of antennas

J Tang, L Jiao, K Zeng, H Wen… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Recently, MIMO (multiple-input-multiple-output) physical layer secure transmission has
attracted great attentions. However, current schemes cannot defend against the passive …

Convolution based feature extraction for edge computing access authentication

F Xie, H Wen, J Wu, S Chen, W Hou… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
In this article, a convolutional neural network (CNN) enhanced radio frequency fingerprinting
(RFF) authentication scheme is presented for Internet of things (IoT). RFF is a non …