The rapid development of information and wireless communication technologies together
with the large increase in the number of end-users have made the radio spectrum more …

Blindly decoding a signal requires estimating its unknown transmit parameters,
compensating for the wireless channel impairments, and identifying the modulation type …

Due to imperfections in transmitters' hardware, wireless signals can be used to verify their
identity in an authorization system. While deep learning was proposed for transmitter …

Robustness against noise is critical for modulation recognition (MR) approaches deployed
in real-world communication systems. In MR systems, a corrupted signal is normally …

In a non-cooperative communication environment, automatic modulation classification
(AMC) is an essential technology for analyzing signals and classifying different kinds of …

In the past decade, deep neural network (DNN) based radio modulation classifications
(RMCs) have outperformed traditional techniques. However, the black-box nature of DNN …

Narrowband Internet of Things (NB-IoT) is an emerging standard serving massive wireless
communications devices. It is implemented based on the legacy long-term evolution (LTE) …

Artificial intelligence (AI) is considered an efficient response to several challenges facing 6G
technology. However, AI still suffers from a huge trust issue due to its ambiguous way of …

UNIVERSITY OF CALIFORNIA Los Angeles UAV Swarm Enabled Communications: System
Design for Spectrum and Energy Efficiency with Sec Page 1 UNIVERSITY OF CALIFORNIA Los …

The spectrum awareness techniques play an important role in IoT networks. It enables
wireless devices or infrastructures to monitor and manage the heterogenous IoT traffics in …