Modulation Classifier

J Roopesh, Amrutha Dc, Meghana Bhushan S N and Keerti Kulkarni

International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2024, vol. 10, issue 3, 199-203

Abstract: In the realm of wireless communications, automatic modulation classification (AMC) plays a crucial role in identifying the modulation type of incoming signals, enabling efficient spectrum usage in congested wireless environments and other communication systems applications. We present an AMC that takes into consideration various parameters among them the 3 major parameters are amplitude, power spectral density (PSD), and Signal to noise ratio (SNR), with the help of machine learning that is Support Vector machine in specific, within the MATLAB environment helps us in classifying the different types of signal that is QPSK, BPSK, QAM, 64QAM and PAM4.Therefore our AMC significantly contributes to the wireless communication by significantly boosting the different modulation techniques and thereby improving the spectrum efficiency.

Keywords: Amplitude values; Power Spectral Density; Signal to Noise Ratio (search for similar items in EconPapers)
Date: 2024
Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT2410319
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Persistent link: https://EconPapers.repec.org/RePEc:jbh:ijsrcs:v10:y2024:i3:id:192

DOI: 10.32628/CSEIT2410319

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