Title :
Identification of voiceband data signal constellations using a divisive cluster algorithm
Author :
Schreyögg, Christoph
Author_Institution :
Res. & Technol., Daimler-Benz AG, Ulm, Germany
Abstract :
A divisive cluster algorithm has been applied to identify the type of signal constellation used by a voice band modem. Tests with simulated signals showed that this cluster technique is capable to classify a variety of voiceband signals in use (DPSK2A/B, DPSK4A/B, V.29, V.29Fallback (7.2 kbit/s) and V.32Fallback (9.6kbit/s)). Compared to former proposed algorithms to classify linear digital modulated signal constellations, this technique is able to classify both higher rated PSK and QAM signals at high to moderate signal-to-noise ratios (SNR). With respect to signal impairments such as phase jitter, residual carrier or incomplete equalisation the classifier has proven to be reasonably robust. This paper describes the applied cluster algorithm and provides examples of its performance
Keywords :
differential phase shift keying; digital communication; identification; jitter; modems; pattern recognition; statistical analysis; telecommunication equipment testing; 7.2 kbit/s; 9.6 kbit/s; DPSK2A/B; DPSK4A/B; PSK signals; QAM signals; SNR; V.29; V.29Fallback; V.32Fallback; cluster analysis; digital communication; divisive cluster algorithm; incomplete equalisation; linear digital modulated signal constellations; performance; phase jitter; residual carrier; signal constellation classification; signal constellation identification; signal impairments; signal to noise ratio; simulated signal tests; statistical pattern recognition; voice band modem; voiceband data signal constellations; Clustering algorithms; Constellation diagram; Digital modulation; Jitter; Modems; Phase shift keying; Quadrature amplitude modulation; Robustness; Signal to noise ratio; Testing;
Conference_Titel :
Digital Signal Processing Workshop Proceedings, 1996., IEEE
Conference_Location :
Loen
Print_ISBN :
0-7803-3629-1
DOI :
10.1109/DSPWS.1996.555565