下一代自适应无线电系统中基于K近邻的自动调制分类器

International Journal of Security and Its Applications Pub Date : 2019-12-31 DOI:10.33832/ijsia.2019.13.4.04

M. Subbarao, P. Samundiswary

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引用次数: 3

摘要

-本文提出了k -近邻(KNN)分类器的真实性以及不同的统计特征，以便对MPSK和MQAM信号进行分类。此外，在非理想信道条件下，分析了不同K值和距离函数的KNN分类器的性能。最后，为了证明所提出的KNN分类器的优越性，在不同信噪比值下与文献方法的性能进行了比较。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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K- Nearest Neighbors based Automatic Modulation Classifier for Next Generation Adaptive Radio Systems

— This paper presents a verity of K-Nearest Neighbors (KNN) classifiers along with different statistical features in order to classify MPSK and MQAM signals. Further, the performance of proposed KNN classifiers with different values of ‘K’ and distance functions are analyzed under non-ideal channel conditions. Finally, to prove the superiority of the proposed KNN classifiers the performance is compared with that of the literature approaches at various SNR values.

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来源期刊

International Journal of Security and Its Applications COMPUTER SCIENCE, INFORMATION SYSTEMS-

自引率

0.00%

发文量

期刊介绍： IJSIA aims to facilitate and support research related to security technology and its applications. Our Journal provides a chance for academic and industry professionals to discuss recent progress in the area of security technology and its applications. Journal Topics: -Access Control -Ad Hoc & Sensor Network Security -Applied Cryptography -Authentication and Non-repudiation -Cryptographic Protocols -Denial of Service -E-Commerce Security -Identity and Trust Management -Information Hiding -Insider Threats and Countermeasures -Intrusion Detection & Prevention -Network & Wireless Security -Peer-to-Peer Security -Privacy and Anonymity -Secure installation, generation and operation -Security Analysis Methodologies -Security assurance -Security in Software Outsourcing -Security products or systems -Security technology -Systems and Data Security