Abstract

Digital modulation techniques are use when the information signal is digital and the information signal is modulated by the amplitude, phase or frequency of a carrier. Various digital modulation techniques are used for various signal transmission. All these techniques provide versatility to the transmission medium and recognizing these modulation schemes is quite useful for the military and COMINT applications. All Digital modulation methods are based on some statistical parameters. Various recognition algorithms have been developed and still developing. The recognition algorithms are divided into two major groups maximum likelihood approach (MLA) and pattern recognition approach (PRA). Aim of this paper to describe different techniques of modulation recognition in brief along with various key features involve in these techniques, including all consideration of transmitter and receiver.

References

• E. E Azzouz and A. K. Nandi, "Automatic Modulation Recognition of Communication Signals", Kluwar Academic Publishers, 1996.
• D. Linda Essentials of cognitive radio, Cambridge Wireless Essentials Series, Cambridge University Press, 2009.
• O. A. Dobre and Y. Bar-Ness Blind Modulation Classification: A Concept Who's Time has Come IEEE/Sarnoff Symposium, pp. 223U? 228 April 18U? 19, 2005.
• D. L. Guen, A. Man sour, "Automatic Recognition Algorithm for Digitally Modulated Signals", International Conference on Signal Processing, Pattern Recognition, and Applications Crete, Greece, 25-28 June,2002.
• K . N. Haq, A. Mansur, Sven Nordholm, "Comparison of digital modulation classification based on statistical approach", 10thPostgraduate Electrical and Computer Symposium Perth Australia, September 2009.
• S. S. Soliman and Z. S. Hsue, "Signal classification using statistical moments,"IEEE Transactions on Communications, vol. 40(5), pp. 908–916, May 1992
• Z. S. Hsue and S. S. Soliman, "Automatic modulation classification using zero-crossing IEEE Proc. Part F, Radar and signal processing, vol. 137 (6), pp. 459–464, December 1990.
• G. Acosta, "OFDM simulation using Mat Lab", Report, Smart Antenna Research Laboratory Georgia Institute of Technology, Georgia, USA, August 2000.
• Li Tieying, Cui yan,"A design of neural classifier based on rough sets" [J]. Computer Engineering and Applications, 2005, 32.
• Adel Metref, Daniel Le Guennec, Jacques Palicot "A new digital modulation recognition technique using the phase detector reliability "2010.
• HU You-qiang, LIU Juan, TAN Xiao-hang "Digital modulation recognition based on instantaneous information "June 2010.
• Fatima K. Faek," Digital Modulation Classification Using Wavelet Transform and Artificial Neural network" (JZS) Journal of Zankoy Suleiman 2010.
• Asoke K. Nandi, E. E. Azzouz "Algorithms for Automatic Modulation Recognition of Communication Signals" IEEE Transactions On Communications, Vol. 46, No. 4, April 1988.
• Liang Hong K. C. Ho" Identification of Digital Modulation Types Using the Wavelet Transform", vol2, pp. 20. 2. 1-20. 2. 6, October 2010.
• Mobien shoaib, Alharbi Harza, Alturki Fahd "Robustness of digital modulated signals against variation in Hf noise model", EURASIP journal on wireless communication network, 2011.
• Wu Min. The research of Rough Set attribute reduction algorithm in numeral character recognition [D]. Hefei University of Technology Master Dissertation, 2009.
• N Ahmadi, ", Modulation classification based on constellation using TTSAS approach", Journal of recognition research, May 2010.
• Zhao F. , Hu Y. and SH. ,Hao, 'Classification using wavelet packet decomposition and support vector machine for digital modulation', Journal of system Engineering and Electronics, August 2009,19,914-918.
• Khandker Nada Haq, Ali Mansour, Sven Nordholm" Recognition of Digital Modulated Signals based on Statistical Parameters ", 4th IEEE International Conference on Digital Ecosystems and Technologies (IEEE DEST 2010).
• Z. S. Hsue and S. S. Soliman, "Automatic modulation classification using zero-crossing IEEE Proc. Part F, Radar and signal processing, vol. 137 (6), pp. 459–464, December 1990.