DocumentCode
3363517
Title
Signal classification and cognitive sensor network
Author
Wei Su
Author_Institution
Commun. Electron. RD&E Center, US Army, Fort Monmouth, NJ
fYear
2009
fDate
26-29 March 2009
Firstpage
2
Lastpage
2
Abstract
Signal classification is an important subject for military radio communications. With the revolution of digitizing communications ever closer to the antenna, commercial cognitive radios with programmable modulation schemes and adaptive transmission rates have become a practical wireless communication platform. Signal classification techniques have attracted much attention recently by the cognitive network applications in developing the next generation radio receivers and sensor networks with built-in automatic signal detection and classification capabilities. However, the technical expectations and goals in commercial applications are quite different with that in military communication systems. A key research area is to develop new algorithms with the low-cost real-time adaptive demodulation capability. An overview of automatic signal classification techniques and the challenges in migrating current signal classification methods into the cognitive radios and sensor network will be discussed.
Keywords
adaptive modulation; cognitive radio; demodulation; military communication; signal classification; wireless sensor networks; adaptive demodulation; adaptive transmission rate; cognitive radio; cognitive sensor network; military radio communication; programmable modulation scheme; signal classification; wireless communication; Adaptive arrays; Cognitive radio; Digital modulation; Military communication; Modulation coding; Next generation networking; Pattern classification; Radio communication; Transmitting antennas; Wireless communication;
fLanguage
English
Publisher
ieee
Conference_Titel
Networking, Sensing and Control, 2009. ICNSC '09. International Conference on
Conference_Location
Okayama
Print_ISBN
978-1-4244-3491-6
Electronic_ISBN
978-1-4244-3492-3
Type
conf
DOI
10.1109/ICNSC.2009.4919229
Filename
4919229
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