Framework of network centric signal sensing for automatic modulation classification

Author

Su, Wei ; Kosinski, John

Author_Institution

US Army Commun.-Electron. RD&E Center, Fort Monmouth, NJ, USA

fYear

2010

fDate

10-12 April 2010

Firstpage

534

Lastpage

539

Abstract

This paper proposes a sensor network framework for sensing and exploiting unknown signals. It includes distributed decision fusion, distributed processing, centralized synchronous signal sensing, centralized asynchronous signal sensing, and system of systems single sensing. Data fusion is applied to enhance the SNR of weak signals and to eliminate channel distortion. Statistical estimation and modulation classification techniques are discussed.

Keywords

sensor fusion; signal classification; statistical analysis; wireless sensor networks; automatic modulation classification; centralized synchronous signal sensing; channel distortion; data fusion; distributed decision fusion; distributed processing; network centric signal sensing; sensor network; statistical estimation; Chromium; Cognitive radio; FCC; Pattern classification; RF signals; Radio transmitters; Sensor fusion; Sensor phenomena and characterization; Signal processing; Wireless communication; cognitive radios; modulation classification; network centric; sensor network; signal sensing;

fLanguage

English

Publisher

ieee

Conference_Titel

Networking, Sensing and Control (ICNSC), 2010 International Conference on

Conference_Location

Chicago, IL

Print_ISBN

978-1-4244-6450-0

Type

conf

DOI

10.1109/ICNSC.2010.5461601

Filename

5461601