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An Automatic Digital Modulation Classifier Using Higher-Order Statistics for Software-Defined Radios

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Congress on Intelligent Systems (CIS 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1334))

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Abstract

Automatic modulation recognition (AMR) plays a vital role in various applications such as software-defined radios (SDRs), cognitive radio (CR) receivers, and surveillance systems. This paper is based on the recognition and classification of digital modulation schemes. The designed system is capable of recognizing nine digital modulation schemes, namely 2FSK, 4FSK, 8FSK, 2PSK, 4PSK, 8PSK, 16QAM, 64QAM, and 256 QAM in additive white Gaussian noise (AWGN) environment. The system includes two steps: feature extraction and classification. In feature extraction step has used seven higher-order cumulants, namely C40, C42, C44 C51, C53, C62, and C80 as features for statistical analysis of signals. In the classification, the step has used the principal component analysis technique on the feature set for compression of data and for classification of different modulation schemes. The simulation results show that the presented system has 100% classification accuracy at 16 dB SNR.

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Author information

Authors and Affiliations

  1. Electronics and Communication Engineering Department, University Institute of Engineering and Technology, Kurukshetra University, Kurukshetra, India

    Nikhil Marriwala & Manisha Ghunsar

Authors
  1. Nikhil Marriwala
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  2. Manisha Ghunsar
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Rajasthan Technical University, Kota, Rajasthan, India

    Harish Sharma

  2. Department of Computer Science and Engineering, Jaypee Institute of Information Technology, Noida, Uttar Pradesh, India

    Mukesh Saraswat

  3. National Institute of Technology, Jalandhar, Punjab, India

    Anupam Yadav

  4. Korea University, Seoul, Korea (Republic of)

    Joong Hoon Kim

  5. South Asian University, New Delhi, Delhi, India

    Jagdish Chand Bansal

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Marriwala, N., Ghunsar, M. (2021). An Automatic Digital Modulation Classifier Using Higher-Order Statistics for Software-Defined Radios. In: Sharma, H., Saraswat, M., Yadav, A., Kim, J.H., Bansal, J.C. (eds) Congress on Intelligent Systems. CIS 2020. Advances in Intelligent Systems and Computing, vol 1334. Springer, Singapore. https://doi.org/10.1007/978-981-33-6981-8_44

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