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2017•Unpublished venueRequires access

Constellation based signal modulation recognition for MQAM

Liu Wang, Yubai Li

Open publisher page 20 citations

Abstract

QAM modulation signal has been widely used in wireless communication system. This paper presents a method of identifying MQAM signals, which is effective even in high-order QAM modulation signals. Owing to different types of modulation signals mapping to different constellations, we propose a constellation-based algorithm. In this paper, we use subtractive clustering algorithm which automatically calculate the center of the constellation, and then according to the number of center points, we can recognize modulation signals. From the simulation results, the method can effective recognize MQAM signals, including: 4QAM, 16QAM, 32QAM, 64QAM, 128QAM, 256QAM. When SNR≥5dB, 99% of 4QAM and 16QAM can be correctly recognized, in addition, for high-order QAM signals 128QAM and 256QAM etc., we have a highly recognition rate when SNR≥15dB.

About this research paper

What this paper is about

QAM modulation signal has been widely used in wireless communication system. This paper presents a method of identifying MQAM signals, which is effective even in high-order QAM modulation signals. Owing to different types of modulation signals mapping to different constellations, we propose a constellation-based algorithm. In this paper, we use subtractive clustering algorithm which automatically calculate the center of the constellation, and then according to the number of center points, we can recognize modulation signals. From the simulation results, the method can effective recognize MQAM signals, including: 4QAM, 16QAM, 32QAM, 64QAM, 128QAM, 256QAM. When SNR≥5dB, 99% of 4QAM and 16QAM can be correctly recognized, in addition, for high-order QAM signals 128QAM and 256QAM etc., we have a highly recognition rate when SNR≥15dB.

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Available abstract

QAM modulation signal has been widely used in wireless communication system. This paper presents a method of identifying MQAM signals, which is effective even in high-order QAM modulation signals. Owing to different types of modulation signals mapping to different constellations, we propose a constellation-based algorithm. In this paper, we use subtractive clustering algorithm which automatically calculate the center of the constellation, and then according to the number of center points, we can recognize modulation signals. From the simulation results, the method can effective recognize MQAM signals, including: 4QAM, 16QAM, 32QAM, 64QAM, 128QAM, 256QAM. When SNR≥5dB, 99% of 4QAM and 16QAM can be correctly recognized, in addition, for high-order QAM signals 128QAM and 256QAM etc., we have a highly recognition rate when SNR≥15dB.

Key concepts: Quadrature amplitude modulation, Constellation diagram, QAM, Computer science, Modulation (music), Constellation, SIGNAL (programming language), Signal-to-noise ratio (imaging)

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