A novel neural network-based method for decoding and detecting of the DS8-PSK scheme in an OCC system
This paper proposes a novel method of training and applying a neural network to act as an
adaptive decoder for a modulation scheme used in optical camera communication (OCC) …
adaptive decoder for a modulation scheme used in optical camera communication (OCC) …
Automatic determination of digital modulation types with different noises using convolutional neural network based on time–frequency information
In this study, a novel digital modulation classification model has been proposed for
automatically recognizing six different modulation types including amplitude shift keying …
automatically recognizing six different modulation types including amplitude shift keying …
[PDF][PDF] Modulation identification algorithm for adaptive demodulator in software defined radios using wavelet transform
P Prakasam, M Madheswaran - International Journal of Signal …, 2009 - idc-online.com
A generalized Digital Modulation Identification algorithm for adaptive demodulator has been
developed and presented in this paper. The algorithm developed is verified using wavelet …
developed and presented in this paper. The algorithm developed is verified using wavelet …
Reconfigurable dual mode IEEE 802.15. 4 digital baseband receiver for diverse IoT applications
IEEE 802.15. 4 takes a center stage in IoT as Low-Rate Wireless Personal Area Networks
(LR-WPANs). The standard specifies Offset Quadrature Phase Shift Keying Physical Layer …
(LR-WPANs). The standard specifies Offset Quadrature Phase Shift Keying Physical Layer …
Convolutional neural network aided signal modulation recognition in OFDM systems
S Hong, Y Wang, Y Pan, H Gu, M Liu… - 2020 IEEE 91st …, 2020 - ieeexplore.ieee.org
Signa1 modulation recognition (SMR) is an essential and challenging topic in orthogonal
frequency-division multiplexing (OFDM) systems, and also it is the fundamental technique …
frequency-division multiplexing (OFDM) systems, and also it is the fundamental technique …
Software defined demodulation of multiple frequency shift keying with dense neural network for weak signal communications
M Kozlenko, V Vialkova - 2020 IEEE 15th International …, 2020 - ieeexplore.ieee.org
In this paper we present the symbol and bit error rate performance of the weak signal digital
communications system. We investigate orthogonal multiple frequency shift keying …
communications system. We investigate orthogonal multiple frequency shift keying …
Differential faster-than-Nyquist signaling
T Ishihara, S Sugiura - IEEE Access, 2018 - ieeexplore.ieee.org
In this paper, we propose a novel differential faster-than-Nyquist (DFTN) signaling concept
that allows us to dispense with any channel estimation at the receiver, while benefiting from …
that allows us to dispense with any channel estimation at the receiver, while benefiting from …
Robust receiver for OFDM-DCSK modulation via rank-1 modeling and ℓp-minimization
In this paper, the problem of receiver design for orthogonal frequency division multiplexing
differential chaos shift keying (OFDM-DCSK) communication systems is addressed. By …
differential chaos shift keying (OFDM-DCSK) communication systems is addressed. By …
Modulation Classification for Overlapped Signals Using Deep Learning
Modulation recognition (MR) plays a pivotal role in tasks encompassing spectrum
management, security enforcement, and interference mitigation. This research work …
management, security enforcement, and interference mitigation. This research work …
Deep-waveform: A learned OFDM receiver based on deep complex-valued convolutional networks
The (inverse) discrete Fourier transform (DFT/IDFT) is often perceived as essential to
orthogonal frequency-division multiplexing (OFDM) systems. In this paper, a deep complex …
orthogonal frequency-division multiplexing (OFDM) systems. In this paper, a deep complex …