• 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