Machine learning for large-scale optimization in 6g wireless networks
The sixth generation (6G) wireless systems are envisioned to enable the paradigm shift from
“connected things” to “connected intelligence”, featured by ultra high density, large-scale …
“connected things” to “connected intelligence”, featured by ultra high density, large-scale …
Deep learning-aided 6G wireless networks: A comprehensive survey of revolutionary PHY architectures
Deep learning (DL) has proven its unprecedented success in diverse fields such as
computer vision, natural language processing, and speech recognition by its strong …
computer vision, natural language processing, and speech recognition by its strong …
SVM-based channel estimation and data detection for one-bit massive MIMO systems
LV Nguyen, AL Swindlehurst… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
The use of low-resolution Analog-to-Digital Converters (ADCs) is a practical solution for
reducing cost and power consumption for massive Multiple-Input-Multiple-Output (MIMO) …
reducing cost and power consumption for massive Multiple-Input-Multiple-Output (MIMO) …
Channel estimation for intelligent reflecting surface aided wireless communications using conditional GAN
Channel estimation is very challenging, especially in an intelligent reflecting surface (IRS)-
aided wireless system. This letter proposes a deep learning (DL) based approach for IRS …
aided wireless system. This letter proposes a deep learning (DL) based approach for IRS …
LSTM-GRU model-based channel prediction for one-bit massive MIMO system
In this article, we propose a deep learning (DL) model to estimate the channel matrix for a
massive multi-input multi-output (MIMO) system with a one-bit analog-to-digital converter …
massive multi-input multi-output (MIMO) system with a one-bit analog-to-digital converter …
[HTML][HTML] Deep learning for joint pilot design and channel estimation in MIMO-OFDM systems
XF Kang, ZH Liu, M Yao - Sensors, 2022 - mdpi.com
In MIMO-OFDM systems, pilot design and estimation algorithm jointly determine the
reliability and effectiveness of pilot-based channel estimation methods. In order to improve …
reliability and effectiveness of pilot-based channel estimation methods. In order to improve …
Large AI model empowered multimodal semantic communications
Multimodal signals, including text, audio, image and video, can be integrated into Semantic
Communication (SC) for providing an immersive experience with low latency and high …
Communication (SC) for providing an immersive experience with low latency and high …
Channel power gain estimation for terahertz vehicle-to-infrastructure networks
The use of terahertz (THz) frequencies has been recommended to achieve high-speed and
ultra-low latency transmissions. Although there exist very large bandwidths in the THz …
ultra-low latency transmissions. Although there exist very large bandwidths in the THz …
Channel estimation for quantized systems based on conditionally Gaussian latent models
This work introduces a novel class of channel estimators tailored for coarse quantization
systems. The proposed estimators are founded on conditionally Gaussian latent generative …
systems. The proposed estimators are founded on conditionally Gaussian latent generative …
On the mean square error optimal estimator in one-bit quantized systems
This article investigates the mean square error (MSE)-optimal conditional mean estimator
(CME) in one-bit quantized systems in the context of channel estimation with jointly …
(CME) in one-bit quantized systems in the context of channel estimation with jointly …