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 …
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) …
CAnet: Uplink-aided downlink channel acquisition in FDD massive MIMO using deep learning
In frequency-division duplexing systems, the downlink channel state information (CSI)
acquisition scheme leads to high training and feedback overhead. In this work, we propose …
acquisition scheme leads to high training and feedback overhead. In this work, we propose …
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 …
Federated edge learning for the wireless physical layer: Opportunities and challenges
Deep learning (DL) has been applied to the physical layer of wireless communication
systems, which directly extracts environment knowledge from data and outperforms …
systems, which directly extracts environment knowledge from data and outperforms …
Communication-efficient personalized federated edge learning for massive mimo csi feedback
Deep learning (DL)-based channel state information (CSI) feedback has garnered
significant research attention in recent years. However, previous research has overlooked …
significant research attention in recent years. However, previous research has overlooked …
AI enlightens wireless communication: A transformer backbone for CSI feedback
X Han, W Zhiqin, L Dexin, T Wenqiang… - China …, 2024 - ieeexplore.ieee.org
This paper is based on the background of the 2nd Wireless Communication Artificial
Intelligence (AI) Competition (WAIC) which is hosted by IMT-2020 (5G) Promotion Group …
Intelligence (AI) Competition (WAIC) which is hosted by IMT-2020 (5G) Promotion Group …
AI enlightens wireless communication: Analyses, solutions and opportunities on CSI feedback
H Xiao, Z Wang, W Tian, X Liu, W Liu… - China …, 2021 - ieeexplore.ieee.org
In this paper, we give a systematic description of the 1st Wireless Communication Artificial
Intelligence (AI) Competition (WAIC) which is hosted by IMT-2020 (5G) Promotion Group …
Intelligence (AI) Competition (WAIC) which is hosted by IMT-2020 (5G) Promotion Group …
Model-driven learning for generic MIMO downlink beamforming with uplink channel information
Accurate downlink channel information is crucial to the beamforming design, but it is difficult
to obtain in practice. This paper investigates a deep learning-based optimization approach …
to obtain in practice. This paper investigates a deep learning-based optimization approach …
PolarDenseNet: A deep learning model for CSI feedback in MIMO systems
In multiple-input multiple-output (MIMO) systems, the high-resolution channel information
(CSI) is required at the base station (BS) to ensure optimal performance, especially in the …
(CSI) is required at the base station (BS) to ensure optimal performance, especially in the …