M-QAM demodulation based on machine learning
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Artigo de evento
Date
2020
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IEEE International Symposium on Broadband Multimedia Systems and Broadcasting, BMSB
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4
Authors
Toledo R.N.
Akamine C.
Jerji F.
Silva L.A.
Akamine C.
Jerji F.
Silva L.A.
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Journal Title
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Volume Title
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Abstract
© 2020 IEEE.This paper presents a new Quadrature Amplitude Modulation (M-QAM) demodulation method using Machine Learning techniques. The new method significantly reduces the demodulation complexity for high-order constellations while maintains the demodulation accuracy. The experimental results demonstrate a performance gain of up to 1485% for 4096-QAM in comparison with the classical Log-Likelihood Ratio demodulator.
Description
Keywords
item.page.scopussubject
Demodulation complexity , Demodulation method , High-order , Log likelihood ratio , Machine learning techniques , On-machines , Performance Gain