@inproceedings{11228dc4be2a43e8895c8890cd23236a,
title = "Classification of interference signals using advanced baseband statistics in pi/4-DQPSK systems",
abstract = "This paper presents a novel technique to classify an interfering signal that can be dual-path propagation, continuous-wave or noise. To identify the dominant interfering signal, a couple of unique statistical features have to be found in the baseband-signal. These features can be used to train a machine-learning algorithm to classify the interference signal. The presented algorithm is tested with a pi/4-DQPSK modulated continuous Terrestrial Trunked Radio (TETRA) downlink. The classification results of several machine learning algorithms are compared to find the most accurate solution.",
author = "M. W{\"o}lfel and U. Bochtler and Eibert, {T. F.} and C. Schmitt",
note = "Publisher Copyright: {\textcopyright} 2018 Electromagnetics Academy. All rights reserved.; 2017 Progress In Electromagnetics Research Symposium - Spring, PIERS 2017 ; Conference date: 22-05-2017 Through 25-05-2017",
year = "2017",
doi = "10.1109/PIERS.2017.8262133",
language = "English",
series = "Progress in Electromagnetics Research Symposium",
publisher = "Electromagnetics Academy",
pages = "2292--2296",
editor = "Chew, {Weng Cho} and Sailing He and Sailing He",
booktitle = "2017 Progress in Electromagnetics Research Symposium - Spring, PIERS 2017",
}