Privacy protection as a major concern of the industrial big data enabling entities makes the
massive safety-critical operation data of a wind turbine unable to exert its great value …

Clinically oriented deep learning algorithms, combined with large-scale medical datasets,
have significantly promoted computer-aided diagnosis. To address increasing ethical and …

Sixth-generation (6G) networks anticipate intelligently supporting a wide range of smart
services and innovative applications. Such a context urges a heavy usage of Machine …

Artificial Intelligence (AI) is expected to play an instrumental role in the next generation of
wireless systems, such as sixth-generation (6G) mobile network. However, massive data …

Benefit from the rapid evolution of artificial intelligence and wireless communication
technology, diverse Internet of Things (IoT) devices with edge computing ability have widely …

Federated learning (FL) is promising in enabling large-scale model training by massive
devices without exposing their local datasets. However, due to limited wireless resources …

Deep learning has been proven to be a powerful tool for addressing the most significant
issues in cognitive radio networks, such as spectrum sensing, spectrum sharing, resource …

Due to the diverse equipment and uneven load distribution in industrial environments, data
regarding faults are often unbalanced. Moreover, data and models from clients may become …

Radio frequency fingerprint identification (RFFI) is a promising physical layer security
technique that employs the hardware-introduced features extracted from the received …

Over-the-air federated learning (AirFL) allows devices to train a learning model in parallel
and synchronize their local models using over-the-air computation. The integrity of AirFL is …