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Wireless Personal Communications
Erschienen in: Wireless Personal Communications 2/2022

11.06.2022

On the Classification of Modulation Schemes Using Higher Order Statistics and Support Vector Machines

verfasst von: Remziye Büsra Coruk, Bengisu Yalcinkaya Gokdogan, Mohamed Benzaghta, Ali Kara

Erschienen in: Wireless Personal Communications | Ausgabe 2/2022

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Abstract

The recognition of modulation schemes in military and civilian applications is a major task for intelligent receiving systems. Various Automatic Modulation Classification (AMC) algorithms have been developed for this purpose in the literature. However, classification with low computational complexity as well as reasonable processing time is still a challenge. In this paper, a feature-based approach along with various classifiers is employed based on statistical features as well as higher-order moments and cumulants. An over-the-air (OTA) recorded dataset consisting of four analog and ten digital modulation schemes are used for testing the proposed method at 0–20 dB SNR. The overall accuracy for quadratic Support Vector Machine (SVM) is found to be as high as 98% at 10 dB. The comparison of the results with other AMC papers published in the literature indicates that the proposed method present higher accuracy, especially for realistic channel induced OTA dataset.
Vorheriger Artikel An Adaptive Lossly Quantization Technique for Key Extraction Applied in Vehicular Communication
Nächster Artikel Design and Analysis of Dual-band Circularly Polarized Hybrid Ring Cylindrical Dielectric Resonator Antenna for Wireless Applications in C and X-Band

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Metadaten
Titel
On the Classification of Modulation Schemes Using Higher Order Statistics and Support Vector Machines
verfasst von
Remziye Büsra Coruk
Bengisu Yalcinkaya Gokdogan
Mohamed Benzaghta
Ali Kara
Publikationsdatum
11.06.2022
Verlag
Springer US
Erschienen in
Wireless Personal Communications / Ausgabe 2/2022
Print ISSN: 0929-6212
Elektronische ISSN: 1572-834X
DOI
https://doi.org/10.1007/s11277-022-09795-8

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