Implementação e análise de técnica para estimação de SNR baseado em Deep Learning

João Henrique Delfino, Juliano Silveira Ferreira, Roberto Kagami, Luciano Leonel Mendes

DOI: 10.14209/sbrt.2023.1570913356

Evento: XLI Simpósio Brasileiro de Telecomunicações e Processamento de Sinais (SBrT2023)

Keywords: Deep Learning NMSE Signal-to-Noise Ratio 6G

Abstract

The researches about radio communication systems, as future 6G networks, look for the implementation of communication links that ensure the quality of service even under adverse conditions. A fundamental metric to analyze communication channel condition is the Signal-to-Noise Ratio. This work presents an implementation approach of an innovative algorithm of estimation for this metric based on artificial intelligence, which provides superior precision to the technique that uses Normalized Mean Squared Error.

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