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AUTOMATIC MODULATION CLASSIFICATION: CUMULANT APPROACH
Bulletin of Russian academy of natural sciences, 2023The article describes the apparatus for determining the types of modulation based on cumulants. A new approach based on cumulants up to the eighth order is considered. The rationale for the use of the cumulant method is given. The results of the application of artificial neural networks in the task of automating the detection of signs of intrapulse ...
V.C. Kurbanaliev, Yu.N. Gorbunov
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Automatic modulation classification in practical wireless channels
2016 International Conference on Information and Communication Technology Convergence (ICTC), 2016Flexible spectrum utilization becomes one of the major agendas in the next generation wireless communications. A core technology to efficiently adjust spectrum is automatic modulation classification (AMC) which recently emerges in various future wireless research including military communications, cognitive radio and high-throughput wireless.
Sung-Jin Kim, Dongweon Yoon
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Automatic modulation classification for underwater acoustic Communications
The 10th IEEE International Symposium on Signal Processing and Information Technology, 2010This paper reviews an approach for the automatic classification of digital modulation in the underwater acoustic environment. The underwater acoustic communication is affected by many factors such as; Doppler spread (so high than that for the radio frequency's communications), noise and multi-path. Any classification technique, applied to recognize the
Nouha Alyaoui +2 more
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Automatic Modulation Classification by Support Vector Machines
2004Automatic classification of analog and digital modulation signals plays an important role in communication applications such as an intelligent demodulator, interference identification and monitoring, so many investigations have been carried out in the past.
Zhijin Zhao +3 more
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Likelihood-Based Automatic Modulation Classification in OFDM With Index Modulation
IEEE Transactions on Vehicular Technology, 2018In orthogonal frequency division multiplexing (OFDM) with index modulation, the modulation parameters to be classified include both the signal constellation and the number of active subcarriers. This is different from conventional OFDM schemes where only the signal constellation needs to be classified.
Jianping Zheng
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Automatic modulation classification using polynomial classifiers
2014 IEEE 25th Annual International Symposium on Personal, Indoor, and Mobile Radio Communication (PIMRC), 2014In this paper, a new automatic modulation classification system using a polynomial classifier is proposed. The feature set used in the proposed system is comprised of second, fourth and sixth higher order cumulants of the received signal. The polynomial classifier expands the feature vector into a higher dimensional space in which the different ...
Ameen Abdelmutalab +2 more
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Combining clustering and SVM for automatic modulation classification
International Journal of Computer Applications in Technology, 2012In this paper, we propose a new modulation classification method based on the combination of clustering and Support Vector Machine (SVM), in which a new algorithm is introduced to extract key features. To recognise signals modulated based on constellation diagram, such as MPSK and MQAM; K-means clustering is adopted for recovering constellation under ...
Aisheng Liu, Qi Zhu
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Automatic modulation classification of digital modulation signals with stacked autoencoders
Digital Signal Processing, 2017Modulation identification of the transmitted signals remain a challenging area in modern intelligent communication systems like cognitive radios. The computation of the distinct features from input data set and applying machine learning algorithms has been a well-known method in the classification of such signals.
Afan Ali, Yangyu Fan, Shu Liu 0002
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Blind automatic modulation classification in multipath fading channels
2017 22nd International Conference on Digital Signal Processing (DSP), 2017Automatic Modulation Classification (AMC) has been deeply studied in the context of Cognitive Radio (CR) where it represents a required step between signal detection and demodulation. Several blind methods were proposed in the case of Additive White Gaussian Noise (AWGN) channels.
Gouldieff, Vincent +2 more
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SNR-Boosted Automatic Modulation Classification
2021 55th Asilomar Conference on Signals, Systems, and Computers, 2021Clayton A. Harper +3 more
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