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Automatic Modulation Classification Based on the Improved AlexNet
2021 International Wireless Communications and Mobile Computing (IWCMC), 2021In the military and civilian domains, the modulation classification in the communication system is an extremely important technology that needs to be constantly updated and improved. In this paper, we present an automatic modulation classification (AMC) model to do modulation classification in 5 typical types of signal modulation BPSK, QPSK, 8PSK ...
Zheao Li, Zhongjin Jiang, Jie Huang 0004
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Real-Time Automatic Modulation Classification
2019 International Conference on Field-Programmable Technology (ICFPT), 2019Deep learning based techniques have shown promising results over traditional hand-crafted methods for automatic modulation classification for radio signals. However, implementation of these deep learning models on specialized hardware can be challenging, as both latency and throughput performance are critical to achieving real-time response to over-the-
Stephen Tridgell +3 more
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Automatic classification of analog modulation schemes
2012 IEEE Radio and Wireless Symposium, 2012This paper discusses automatic modulation classification (AMC) of analog schemes. Histograms of instantaneous frequency are used as classification features and Support Vector Machines (SVMs) are then applied to classify the unknown modulation schemes. This novel machine-learning based method can insure robustness in a wide range of SNR.
Haifeng Xiao +3 more
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Likelihood-Ratio Approaches to Automatic Modulation Classification
IEEE Transactions on Systems, Man and Cybernetics, Part C: Applications and Reviews, 2011Adaptive modulation and automatic modulation classification are highly demanded in software-defined radio (SDR) for both commercial and military applications. Various design options of automatic classifiers have attracted researchers in developing 3G and 4G wireless communication systems.
Mengchu Zhou
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Complex-Valued Networks for Automatic Modulation Classification
IEEE Transactions on Vehicular Technology, 2020Deep learning (DL) has been recognized as an effective solution for automatic modulation classification (AMC). However, most recent DL based AMC works are based on real-valued operations and representations. In this correspondence, we aim to demonstrate the high potential of complex-valued networks for AMC. We present the design of several key building
Ya Tu +3 more
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Automatic Modulation Classification in the Presence of Interference
2019 European Conference on Networks and Communications (EuCNC), 2019A modulation recognition method based on a con-volutional neural network (CNN) architecture is assessed through classification of synthetic baseband signals in the presence of a second interfering signal source. The complexity and adaptability of CNNs is leveraged so as to forgo statistical feature extraction procedures and efficiently classify based ...
P. Triantaris +3 more
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Multistage Clustering Based Automatic Modulation Classification
2019 IEEE 89th Vehicular Technology Conference (VTC2019-Spring), 2019Automatic modulation classification (AMC) is the problem of identifying the modulation type of a given radio frequency (RF) signal. This operation is one of the key steps in a cognitive radio based spectrum sharing communication network. It is known that the optimal classification algorithms for AMC are computationally intensive which renders real-time
Lamia M. Kalam +1 more
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Investigation of automatic analog modulation classification algorithms
2012 20th Signal Processing and Communications Applications Conference (SIU), 2012In this paper, feature based modulation classifiers are investigated for AM, DSB, LSB, USB and FM analog modulations methods. Instantaneous phase, magnitude and spectrum of the signals to be classified are used for the calculation of the key features. At the decision step decision tree, minimum distance classifier and support vector machines are used ...
Mehmet Kabasakal, Cenk Toker
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Distributed Automatic Modulation Classification with Compressed Data
MILCOM 2019 - 2019 IEEE Military Communications Conference (MILCOM), 2019This work presents an approach for performing automatic modulation classification (AMC) in a distributed environment using a novel multi-input averaging Convolutional Neural Network (CNN) which ingests one instance of raw received data, in Inphase/Quadrature (IQ) format, and compressed realizations of the same signal from neighboring nodes.
Lauren J. Wong +3 more
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Automatic modulation classification for rapid radio deployment
Proceedings of 2010 21st IEEE International Symposium on Rapid System Protyping, 2010Cognitive Radio and signal intelligence (SIGINT) applications require radios to perform situation-awareness functions, as spectrum sensing to detect the spectral occupation. In more advanced systems, for SIGINT and for interference cancellation purposes, a radio receiver may need to classify an otherwise unknown signal without prior information about ...
Adolfo Recio +2 more
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