Intelligent and reliable deep learning LSTM neural networks-based OFDM-DCSK demodulation design
Chaos communications have widely been applied to provide secure, and anti-jamming
transmissions by exploiting the irregular chaotic behavior. However, the real-valued chaotic …
transmissions by exploiting the irregular chaotic behavior. However, the real-valued chaotic …
Low-feedback sampling rate digital predistortion using deep neural network for wideband wireless transmitters
X Hu, Z Liu, W Wang, M Helaoui… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
In this paper, a low-feedback-sampling-rate digital predistortion (DPD) method is proposed
for wideband wireless transmitters and radio-frequency power amplifiers (PAs). This DPD …
for wideband wireless transmitters and radio-frequency power amplifiers (PAs). This DPD …
Single-channel demodulation algorithm for non-cooperative PCMA signals based on neural network
C Wei, H Peng, J Fan - … on Internet and Information Systems (TIIS), 2019 - koreascience.kr
Aiming at the high complexity of traditional single-channel demodulation algorithm for PCMA
signals, a new demodulation algorithm based on neural network is proposed to reduce the …
signals, a new demodulation algorithm based on neural network is proposed to reduce the …
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 …
Symbol denoising in high order M-QAM using residual learning of deep CNN
This paper presents an integrating concept of de-noising convolutional neural networks
(DnCNN) with quadrature amplitude modulation (QAM) for symbol denoising. DnCNN is …
(DnCNN) with quadrature amplitude modulation (QAM) for symbol denoising. DnCNN is …
Performance analysis of direct-learning digital predistortion with loop delay mismatch in wideband transmitters
Y Liu, X Quan, W Pan, S Shao… - IEEE Transactions on …, 2015 - ieeexplore.ieee.org
Orthogonal frequency-division multiplexing (OFDM) modulation, which is commonly used in
modern digital communication systems due to its flexibility and high spectral efficiency, is …
modern digital communication systems due to its flexibility and high spectral efficiency, is …
Multiple symbol detection for convolutional coded O-QPSK signals in smart metering utility networks without channel state information
G Zhang, H Li, C Han, C Shi, X Zhang - Physical Communication, 2021 - Elsevier
In this paper, a multiple symbol detection (MSD) algorithm is proposed for convolutional
coded offset quadrature phase shift keying (O-QPSK) in IEEE 802.15. 4 g smart metering …
coded offset quadrature phase shift keying (O-QPSK) in IEEE 802.15. 4 g smart metering …
DemodNet: Learning soft demodulation from hard information using convolutional neural network
S Zheng, X Zhou, S Chen, P Qi, C Lou… - ICC 2022-IEEE …, 2022 - ieeexplore.ieee.org
Soft demodulation is a basic module of traditional communication receivers. It converts
received symbols into soft bits, that is, log likelihood ratios (LLRs). However, in the non-ideal …
received symbols into soft bits, that is, log likelihood ratios (LLRs). However, in the non-ideal …
Blind Symbol Rate Estimation using Convolutional Neural Networks for PSK Modulated Signals
J Kodithuwakkuge, V Sekhar… - 2021 15th International …, 2021 - ieeexplore.ieee.org
The problem of symbol rate estimation in Phase Shift Keying (PSK) modulated signals is
addressed. We show that machine learning based techniques can be used to estimate the …
addressed. We show that machine learning based techniques can be used to estimate the …
M-QAM demodulation based on machine learning
RN Toledo, C Akamine, F Jerji… - 2020 IEEE International …, 2020 - ieeexplore.ieee.org
This paper presents a new Quadrature Amplitude Modulation (M-QAM) demodulation
method using Machine Learning techniques. The new method significantly reduces the …
method using Machine Learning techniques. The new method significantly reduces the …