Semantic communications for future internet: Fundamentals, applications, and challenges

W Yang, H Du, ZQ Liew, WYB Lim… - … Surveys & Tutorials, 2022 - ieeexplore.ieee.org
With the increasing demand for intelligent services, the sixth-generation (6G) wireless
networks will shift from a traditional architecture that focuses solely on a high transmission …

A survey of blockchain and artificial intelligence for 6G wireless communications

Y Zuo, J Guo, N Gao, Y Zhu, S **… - … Surveys & Tutorials, 2023 - ieeexplore.ieee.org
The research on the sixth-generation (6G) wireless communications for the development of
future mobile communication networks has been officially launched around the world. 6G …

Overview of deep learning-based CSI feedback in massive MIMO systems

J Guo, CK Wen, S **, GY Li - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Many performance gains achieved by massive multiple-input and multiple-output depend on
the accuracy of the downlink channel state information (CSI) at the transmitter (base station) …

Deep source-channel coding for sentence semantic transmission with HARQ

P Jiang, CK Wen, S **, GY Li - IEEE transactions on …, 2022 - ieeexplore.ieee.org
Recently, semantic communication has been brought to the forefront because deep learning
(DL)-based methods, such as Transformer, have achieved great success in semantic …

AI empowered wireless communications: From bits to semantics

Z Qin, L Liang, Z Wang, S **, X Tao… - Proceedings of the …, 2024 - ieeexplore.ieee.org
Artificial intelligence (AI) and machine learning (ML) have shown tremendous potential in
resha** the landscape of wireless communications and are, therefore, widely expected to …

Interference management for integrated sensing and communication systems: A survey

Y Niu, Z Wei, L Wang, H Wu… - IEEE Internet of Things …, 2024 - ieeexplore.ieee.org
Emerging applications such as autonomous driving and Internet of things (IoT) services put
forward the demand for simutaneous sensing and communication functions in the same …

Application of reinforcement learning and deep learning in multiple-input and multiple-output (MIMO) systems

M Naeem, G De Pietro, A Coronato - Sensors, 2021 - mdpi.com
The current wireless communication infrastructure has to face exponential development in
mobile traffic size, which demands high data rate, reliability, and low latency. MIMO systems …

Binarized aggregated network with quantization: Flexible deep learning deployment for CSI feedback in massive MIMO systems

Z Lu, X Zhang, H He, J Wang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Massive multiple-input multiple-output (MIMO) is one of the key techniques to achieve better
spectrum and energy efficiency in 5G system. The channel state information (CSI) needs to …

CSI-GPT: Integrating generative pre-trained transformer with federated-tuning to acquire downlink massive MIMO channels

Y Zeng, L Qiao, Z Gao, T Qin, Z Wu… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
In massive multiple-input multiple-output (MIMO) systems, how to reliably acquire downlink
channel state information (CSI) with low overhead is challenging. In this work, by integrating …

A Scalable Deep Learning Framework for Dynamic CSI Feedback with Variable Antenna Port Numbers

YC Lin, TS Lee, Z Ding - IEEE Transactions on Wireless …, 2023 - ieeexplore.ieee.org
Transmitter-side channel state information (CSI) is vital for large MIMO downlink systems to
achieve high spectrum and energy efficiency. Existing deep learning architectures for …