Details

Autor(en) / Beteiligte

• Wang, Keren
• Li, Weihao

Titel

A Fast Deep-Learning Signal Detection Architecture for the Short-wave Band

Ist Teil von

• Journal of physics. Conference series, 2020-09, Vol.1646 (1), p.12003

Ort / Verlag

IOP Publishing

Erscheinungsjahr

2020

Link zum Volltext

Quelle

EZB Electronic Journals Library

Beschreibungen/Notizen

• Wideband signal detection plays an important role in wireless communication systems. In recent years, deep learning (DL) has been introduced, and many trial efforts have been posed. In this paper, a fast deep-learning signal detection architecture is proposed for the short-wave band, which consists of the GPU-based Down Digital Converter (DDC), the DL-based signal detector, and the signal data viewer & recorder. Wideband signal data are taken directly as the input, and detected signals are automatically recorded as the output of the architecture. Experimental results suggest that our architecture is capable of detecting signals in the whole short-wave band in quasi-real-time, and specifically, with single GPU device.