Automatic Modulation Classification Based on CNN-Transformer Graph Neural Network [PDF]
Sensors, 2023 In recent years, neural network algorithms have demonstrated tremendous potential for modulation classification. Deep learning methods typically take raw signals or convert signals into time–frequency images as inputs to convolutional neural networks ...
Dong Wang +4 more
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Efficient Cumulant-Based Automatic Modulation Classification Using Machine Learning [PDF]
SensorsThis paper introduces a new technique for automatic modulation classification (AMC) in Cognitive Radio (CR) networks. The method employs a straightforward classifier that utilizes high-order cumulant for training.
Ben Dgani, Israel Cohen
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Automatic Modulation Classification of Digital Communication Signals Using SVM Based on Hybrid Features, Cyclostationary, and Information Entropy [PDF]
Entropy, 2019 Since digital communication signals are widely used in radio and underwater acoustic systems, the modulation classification of these signals has become increasingly significant in various military and civilian applications.
Yangjie Wei, Shiliang Fang, Xiaoyan Wang
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A Deep Learning Framework for Signal Detection and Modulation Classification [PDF]
Sensors, 2019 Deep learning (DL) is a powerful technique which has achieved great success in many applications. However, its usage in communication systems has not been well explored.
Xiong Zha +4 more
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Modulation Classification Using Compressed Sensing and Decision Tree–Support Vector Machine in Cognitive Radio System [PDF]
Sensors, 2020 In this paper, a blind modulation classification method based on compressed sensing using a high-order cumulant and cyclic spectrum combined with the decision tree−support vector machine classifier is proposed to solve the problem of low ...
Xiaoyong Sun +4 more
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Distributed Hybrid Two-Stage Multi-Sensor Fusion for Cooperative Modulation Classification in Large-Scale Wireless Sensor Networks [PDF]
Sensors, 2019 Recent studies showed that the performance of the modulation classification (MC) is considerably improved by using multiple sensors deployed in a cooperative manner.
Goran B. Markovic +2 more
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Application of deep learning algorithms and architectures in the new generation of mobile networks [PDF]
Serbian Journal of Electrical Engineering, 2021 Operators of modern mobile networks are faced with significant challenges in providing the requested level of service to an ever increasing number of user entities. Advanced machine learning techniques based on deep architectures and appropriate
Dašić Dejan +4 more
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Deep Learning for Recognition of Digital Modulations: A Detailed Study [PDF]
AUT Journal of Electrical Engineering, 2022 The automatic modulation recognition of the received signal is very attractive in both military and civilian applications. In the recent years, deep learning techniques have received much attention due to their excellent performance in signal, audio ...
MohammadMohsen Jadidi, Abbas Mohammadi
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Dependable modulation classifier explainer with measurable explainability
Frontiers in Big Data, 2023 The Internet of Things (IoT) plays a significant role in building smart cities worldwide. Smart cities use IoT devices to collect and analyze data to provide better services and solutions.
Gaurav Duggal +2 more
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The Performance Evaluation of Big Data-Driven Modulation Classification in Complex Environment
IEEE Access, 2021 With the proliferation of frequency-using devices and the advent of the era of big data, spectrum management and control are faced with challenges of effectiveness and accuracy.
Zhuoran Cai, Jidong Wang, Minghuan Ma
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