An End-to-End Deep Learning Framework for Wideband Signal Recognition

An End-to-End Deep Learning Framework for Wideband Signal Recognition

Successful management of the radio spectrum requires, as a first step, detailed information about spectrum occupancy. In this work, we present an end-to-end deep learning (DL) based framework to obtain information from wide spectrum bands through signal detection, localization, and modulation classi...

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Bibliographic Details
Main Authors: Adela Vagollari, Martin Hirschbeck, Wolfgang Gerstacker
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Automatic modulation classification
RF spectrum monitoring
spectrum sensing
wideband recognition dataset
wideband signal detection
YOLO object detector
Online Access:https://ieeexplore.ieee.org/document/10136722/

Internet

https://ieeexplore.ieee.org/document/10136722/

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