@inproceedings{a1b720e38ad642b1a2969c97af59557f,
title = "Discrete likelihood ratio test for intelligent signal recognition in software defined radio",
abstract = "Only very few computational complexity reduced automatic modulation recognition methods have been invented to satisfy the seamless demodulation requirement arising from software defined radio (SDR). Among them, a discrete likelihood ratio test (DLRT) based rapid estimation approach was introduced recently in our prior work and capable of identifying most of M-ary linear digital modulation schemes blindly in real-time. This paper intends to present its comprehensive performance evaluation results with a variety of classification cases.",
keywords = "Adaptive modulation, Maximum likelihood ratio test, Modulation classification, Modulation recognition, Software defined radio",
author = "Xu, \{Jefferson L.\} and Zhou, \{Meng Chu\} and Wei Su",
year = "2010",
doi = "10.1109/WOCC.2010.5510597",
language = "English (US)",
isbn = "9781424475964",
series = "WOCC2010 Technical Program - The 19th Annual Wireless and Optical Communications Conference: Converging Communications Around the Pacific",
booktitle = "WOCC2010 Technical Program - The 19th Annual Wireless and Optical Communications Conference",
note = "19th Annual Wireless and Optical Communications Conference, WOCC2010: Converging Communications Around the Pacific ; Conference date: 14-05-2010 Through 15-05-2010",
}