M-QAM demodulation based on machine learning

Tipo
Artigo de evento
Data de publicação
2020
Periódico
IEEE International Symposium on Broadband Multimedia Systems and Broadcasting, BMSB
Citações (Scopus)
4
Autores
Toledo R.N.
Akamine C.
Jerji F.
Silva L.A.
Orientador
Título da Revista
ISSN da Revista
Título de Volume
Membros da banca
Programa
Resumo
© 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.
Descrição
Palavras-chave
Assuntos Scopus
Demodulation complexity , Demodulation method , High-order , Log likelihood ratio , Machine learning techniques , On-machines , Performance Gain
Citação
DOI (Texto completo)
10.1109/BMSB49480.2020.9379442
URI
https://dspace.mackenzie.br/handle/10899/34887
Coleções
Artigo de evento