ATSC 3.0 Constellation Analysis using Computer Vision Combined with AI Decision Tree

Artigo de evento
Data de publicação
2023 31st International Conference on Software, Telecommunications and Computer Networks, SoftCOM 2023
Citações (Scopus)
Almeida J.J.H.
Lopes P.B.
Akamine C.
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© 2023 University of Split, FESB.This paper presents a proposal of a computer vision tool based on Open CV that allows the pre-visual identification of non-uniform constellation levels, channel coding, and Signal-to-Noise Ratio (SNR) estimation on ATSC. Nowadays, the challenge of digital television systems is to transmit high quality videos employing the new technologies, such as Ultra High Definition (UHD). Thus, the new standards as ATSC 3.0 have incorporated several modifications on their physical layers. Among them, it is possible to highlight the use of non-uniform constellations, advanced channel error coding and layer division multiplexing (LDM). However, the pre-visual understanding of the received constellations has become hard since the complex symbols are not distributed evenly in the complex plane and there are different layers to be seen simultaneously. So, the techniques of computer vision have a great potential to analyze and to extract an initial information from the images related to the received constellation, to identify the modulation level, channel coding rate and SNR to each layer, without the necessity of complete demodulation.
Assuntos Scopus
ATSC , Channel signals , High definition , High-quality videos , Non-uniform constellations , Physical layers , Signalto- noise ratio estimations , Ultra-high , Vision tools , Visual identification