NDLI: Automatic Classification of Joint Analog and Digital Communication Signals in Blind Enviroment

Content Provider	IEEE Xplore Digital Library
Author	Yu, Zaihe Shi, Yun Q. Su, Wei
Copyright Year	2007
Description	Author affiliation: Dept. of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, New Jersey, USA (Yu, Zaihe; Shi, Yun Q.) \|\| Intelligence and Information Warfare Directorate, U.S. Army RDECOM CERDEC, Fort Monmouth, New Jersey, USA (Su, Wei)
Abstract	This paper presents a novel algorithm to automatically classify communication signals with unknown modulation type and modulation parameters. This algorithm classifies the modulation type by detecting the presence of cyclostationarities and examining five features derived from the spectrum of the received communication signal. In detecting the presence of the cyclostationarities of the input signal, it utilizes normalized thresholds, which are much reliable under different SNR conditions for different modulation types and modulation parameters. The five features based on the spectrum are designed in such a way that the decisions are made by checking which one is larger or largest - therefore, the task of selecting feature thresholds has been avoided. The above make the developed algorithm more practical, especially in blind environments. The algorithm is capable of recognizing the concrete modulation type if the input is an analog communication signal or an exponentially modulated digital communication signal. For a linearly modulated digital communication signal, the algorithm will classify it into one of several subsets of modulation types. In addition, it provides a very good estimate of the symbol rate for a linearly modulated digital communication signal and a very good estimate of the frequency deviation for an exponentially modulated digital communication signal. The developed algorithm has been tested with data generated by hardware generators, and has been demonstrated to be able to achieve promising.
Starting Page	1
Ending Page	6
File Size	265861
Page Count	6
File Format	PDF
ISBN	9781424415120
DOI	10.1109/MILCOM.2007.4454872
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-10-29
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Digital communication Digital modulation Frequency estimation Chirp modulation Concrete Classification algorithms Signal to noise ratio Analog computers Testing Hardware
Content Type	Text
Resource Type	Article

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