![]() AMC systems were introduced in military and in a short time appeared in commercial applications. The ability to automatically detect the modulation type is crucial for monitoring wireless communication but also for effective signal jamming.Īutomatic Modulation Classification (AMC) is an approach to identify the modulation type and its parameters such as the carrier frequency or symbol rate. From the beginning there has been a strong demand from the military for software defined radios capable of intercepting and decoding various radio transmissions. The concept of the software defined radio has been extensively studied since the late nineties. Nowadays, SDR is becoming the dominant technology in radio communications. Such a design produces a system which can receive and transmit different radio modulations based solely on the software’s specification. ![]() ![]() amplifiers, mixers, filters, demodulators, etc.) were replaced by means of software. SDR is a radio communication system where the traditional radio components (e.g. With the rising popularity of software defined radios (SDR), there is a strong demand for automatic detection of the modulation type and the signal parameters. The proposed approach is tested on both artificial and real samples captured by the SDR. The paper discusses the relevance of different signal features and its impact on the success rate of the neural network classification. A set of signal features are provided as an input of the neural network. This paper presents a modulation classification driven by a neural network. In civil applications, it can be used, e.g., by the amateur radio operators to automatically set the transceiver to the appropriate modulation and communication protocol. In electronic warfare, it enables real-time signal interception and processing. Automatic modulation classification is an approach to identify the modulation type and its parameters such as the carrier frequency or symbol rate. With the rising popularity of Software Defined Radios (SDR), there is a strong demand for automatic detection of the modulation type and signal parameters.
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