Deep learning for signal demodulation in physical layer wireless communications: Prototype platform, open dataset, and analytics
In this paper, we investigate deep learning (DL)-enabled signal demodulation methods and
establish the first open dataset of real modulated signals for wireless communication …
establish the first open dataset of real modulated signals for wireless communication …
Signal demodulation with machine learning methods for physical layer visible light communications: Prototype platform, open dataset, and algorithms
In this paper, we investigate the design and implementation of machine learning (ML)-based
demodulation methods in the physical layer of visible light communication (VLC) systems …
demodulation methods in the physical layer of visible light communication (VLC) systems …
End-to-end PSK signals demodulation using convolutional neural network
WJ Chen, J Wang, JQ Li - IEEE Access, 2022 - ieeexplore.ieee.org
Demodulation techniques are of central importance for achieving intelligent receiving.
Improvement in demodulation performance enhances the overall performance of a …
Improvement in demodulation performance enhances the overall performance of a …
LSTM attention neural-network-based signal detection for hybrid modulated Faster-Than-Nyquist optical wireless communications
M Cao, R Yao, J Xia, K Jia, H Wang - Sensors, 2022 - mdpi.com
In order to improve the accuracy of signal recovery after transmitting over atmospheric
turbulence channel, a deep-learning-based signal detection method is proposed for a faster …
turbulence channel, a deep-learning-based signal detection method is proposed for a faster …
Modulation and classification of mixed signals based on deep learning
J Xu, Z Lin - arXiv preprint arXiv:2205.09916, 2022 - arxiv.org
With the rapid development of information nowadays, spectrum resources are becoming
more and more scarce, leading to a shift in the research direction from the modulation …
more and more scarce, leading to a shift in the research direction from the modulation …
Recurrent Neural Network Based Single-Input/Multi-Output Demodulator for Cochannel Signals
X Cai, W Deng, J Yang, Z Huang - IEEE Communications …, 2023 - ieeexplore.ieee.org
In this letter, a data-driven single-input/multi-output (SIMO) demodulator is proposed, to
demodulate concurrently cochannel signals. The SIMO demodulation is formed as a signal …
demodulate concurrently cochannel signals. The SIMO demodulation is formed as a signal …
Signal demodulator based on in‐phase and quadrature interference‐robust feature
W Deng, X Cai, X Wang, Z Huang - Electronics Letters, 2023 - Wiley Online Library
This letter examines the issue of mitigating strong co‐channel interference in communication
systems is addressed. Unlike conventional model‐based methods, a novel data‐driven …
systems is addressed. Unlike conventional model‐based methods, a novel data‐driven …
单通道通信信号盲分离方法的研究进展综述
邓文， 黄知涛， 王翔 - 通信学报, 2023 - infocomm-journal.com
单通道盲信号分离(SCBSS) 技术相关理论与实践应用不断完善, SCBSS 方法的研究取得了较大
的进展. 在分析国内外大量学术研究成果的基础上, 基于通信信号盲信号分离(BSS) …
的进展. 在分析国内外大量学术研究成果的基础上, 基于通信信号盲信号分离(BSS) …
A signal demodulation algorithm based on generative adversarial networks
W Lijun, Z Minghong, H Yu, S Lei - 2021 IEEE 3rd International …, 2021 - ieeexplore.ieee.org
In recent years, extensive research has been done to obtain better demodulation
performance by combining signal demodulation with deep learning algorithms, such as …
performance by combining signal demodulation with deep learning algorithms, such as …
Recurrent network with attention for symbol detection in communication systems
K Chia, VM Baskaran, KS Wong… - … on Intelligent Signal …, 2022 - ieeexplore.ieee.org
One major challenge for wireless receivers to maintain information fidelity involves the
demodulation of faded signals in noisy environments. Typical demodulation techniques for …
demodulation of faded signals in noisy environments. Typical demodulation techniques for …