Abstract In this paper, a procedure for automatic classification among three types of QAM signals in presence of channel impairments is proposed. A combination of digital signal processing and pattern recognition methods is used for solving the classification problem. The proposed algorithm has been tested by computer simulations and has proven to be reliable and robust against the expected channel impairments such as noise and fading. It is found that all digital modulation types of interest have been correctly classified with a success rate > 91 % at signal-to-noise ratio (SNR) of 14 dB.
Helaly, T., & Elbarbary, K. (2006). AUTOMATIC CLASSIFICATION OF QUADRATURE AMPLITUDE MODULATED (QAM) SIGNALS IN PRESENCE OF CHANNEL IMPAIRMENTS. The International Conference on Electrical Engineering, 5(5th International Conference on Electrical Engineering ICEENG 2006), 1-11. doi: 10.21608/iceeng.2006.33694
MLA
Tarek Helaly; Khairy Elbarbary. "AUTOMATIC CLASSIFICATION OF QUADRATURE AMPLITUDE MODULATED (QAM) SIGNALS IN PRESENCE OF CHANNEL IMPAIRMENTS", The International Conference on Electrical Engineering, 5, 5th International Conference on Electrical Engineering ICEENG 2006, 2006, 1-11. doi: 10.21608/iceeng.2006.33694
HARVARD
Helaly, T., Elbarbary, K. (2006). 'AUTOMATIC CLASSIFICATION OF QUADRATURE AMPLITUDE MODULATED (QAM) SIGNALS IN PRESENCE OF CHANNEL IMPAIRMENTS', The International Conference on Electrical Engineering, 5(5th International Conference on Electrical Engineering ICEENG 2006), pp. 1-11. doi: 10.21608/iceeng.2006.33694
VANCOUVER
Helaly, T., Elbarbary, K. AUTOMATIC CLASSIFICATION OF QUADRATURE AMPLITUDE MODULATED (QAM) SIGNALS IN PRESENCE OF CHANNEL IMPAIRMENTS. The International Conference on Electrical Engineering, 2006; 5(5th International Conference on Electrical Engineering ICEENG 2006): 1-11. doi: 10.21608/iceeng.2006.33694
)
View on SCiNiTO