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Semantic communications for future internet: Fundamentals, applications, and challenges
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 …
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
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 …
future mobile communication networks has been officially launched around the world. 6G …
Overview of deep learning-based CSI feedback in massive MIMO systems
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) …
the accuracy of the downlink channel state information (CSI) at the transmitter (base station) …
Deep source-channel coding for sentence semantic transmission with HARQ
Recently, semantic communication has been brought to the forefront because deep learning
(DL)-based methods, such as Transformer, have achieved great success in semantic …
(DL)-based methods, such as Transformer, have achieved great success in semantic …
AI empowered wireless communications: From bits to semantics
Artificial intelligence (AI) and machine learning (ML) have shown tremendous potential in
resha** the landscape of wireless communications and are, therefore, widely expected to …
resha** the landscape of wireless communications and are, therefore, widely expected to …
Interference management for integrated sensing and communication systems: A survey
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 …
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
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 …
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
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 …
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
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 …
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
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 …
achieve high spectrum and energy efficiency. Existing deep learning architectures for …