Title :
An enhanced SOFM method for automatic recognition and identification of digital modulations
Author_Institution :
Commun. Test Oper., Agilent Technol. Singapore Pte. Ltd., Singapore
Abstract :
This paper enhances the author´s previous work with adding memory and other methods to SOFM recognition system to speed up the process and improve the accuracy of the automatically recognition. The focus of this research is the various M-ary QAM and PSK modulated signal formats subjected to data contamination by noise and fading. Distinguish from other studies, the complexity of nonlinear channel situations and certain critical use cases have been considered in the estimation of the unknown constellation. Successful recognition results have been achieved with low SNR for BPSK, QPSK, PSK-16 and QAM-16, and modest SNR from 10 to 20 dB for higher-level QAM schemes up to QAM-256.
Keywords :
fading; learning (artificial intelligence); noise; pattern recognition; quadrature amplitude modulation; quadrature phase shift keying; self-organising feature maps; telecommunication computing; 10 to 20 dB; BPSK; PSK modulated signal formats; PSK-16; QAM-16; QAM-256; QPSK; SNR; automatic identification; automatic recognition; binary phase shift keying; data contamination; digital modulations; fading; noise; nonlinear channel situations; phase shift keying; quadrature amplitude modulation; quadrature phase shift keying; self organizing feature maps; signal-to-noise ratio; AWGN; Additive white noise; Binary phase shift keying; Digital modulation; Frequency; Gaussian noise; Phase shift keying; Quadrature amplitude modulation; Quadrature phase shift keying; Signal to noise ratio;
Conference_Titel :
Electronic Design, Test and Applications, Proceedings. DELTA 2004. Second IEEE International Workshop on
Conference_Location :
Perth, WA, Australia
Print_ISBN :
0-7695-2081-2
DOI :
10.1109/DELTA.2004.10037