The emerging physical-layer unclonable attribute-aided authentication (PLUA) schemes are
capable of outperforming traditional isolated approaches, with the advantage of having …

Aiming at the problem of poor prediction accuracy of Channel State Information (CSI)
caused by fast time-varying channels in wireless communication systems, this paper …

This paper investigates deep learning techniques to predict transmit beamforming based on
only historical channel data without current channel information in the multiuser multiple …

The advent of sixth-generation (6 G) wireless communications has posed significant
challenges to channel modeling. Channel measurements cannot cover all scenarios and …

The challenges and resilience of vehicular ad hoc network (VANET) and deep neural
network (DNN) hybrid architectures in terms of reliability in smart cities have attracted much …

Establishing and maintaining 5G mmWave vehicular connectivity poses a significant
challenge due to high user mobility that necessitates frequent triggering of beam switching …

Ultrasound is extremely efficient for wireless signal transmission through metal barriers due
to no limit of the Faraday shielding effect. Echoing in the ultrasonic channel is one of the …

This paper introduces a novel prediction method for spatio-temporal non-stationary
channels between unmanned aerial vehicles (UAVs) and ground control vehicles, essential …

Accurate channel state information (CSI) estimation is helpful for reliable transmission in
high mobility communication scenarios, in which the channel being highly time-varying and …

This paper proposes a deep learning-based channel estimation method for multiple-input
multiple-output (MIMO) systems in spatially correlated channels. To reduce the pilot …