Generative AI for integrated sensing and communication: Insights from the physical layer perspective

J Wang, H Du, D Niyato, J Kang, S Cui… - IEEE Wireless …, 2024 - ieeexplore.ieee.org
As generative artificial intelligence (GAl) models continue to evolve, their generative
capabilities are increasingly enhanced, and being used exten-sively in content generation …

Generative AI for physical layer communications: A survey

N Van Huynh, J Wang, H Du, DT Hoang… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
The recent evolution of generative artificial intelligence (GAI) leads to the emergence of
groundbreaking applications such as ChatGPT, which not only enhances the efficiency of …

Learning and adaptation for millimeter-wave beam tracking and training: A dual timescale variational framework

M Hussain, N Michelusi - IEEE Journal on Selected Areas in …, 2021 - ieeexplore.ieee.org
Millimeter-wave vehicular networks incur enormous beam-training overhead to enable
narrow-beam communications. This paper proposes a learning and adaptation framework in …

Beam Management Technique For 5G Wireless Communication: A Deep Learning Approach

S Pawar, M Venkatesan - 2022 IEEE Conference on …, 2022 - ieeexplore.ieee.org
The expectation from next-generation 5G technology is to satisfy data-hungry applications
such as vehicular applications and augmented and virtual reality. 5G along with millimeter …