使用分裂聚类算法识别语音波段数据信号星座

C. Schreyogg
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引用次数: 5

摘要

应用分裂聚类算法来识别语音波段调制解调器所使用的信号星座类型。对模拟信号的测试表明,该聚类技术能够对使用的各种语音频段信号(DPSK2A/B、DPSK4A/B、V.29、V.29 fallback (7.2 kbit/s)和V.32Fallback (9.6kbit/s))进行分类。与先前提出的线性数字调制信号星座分类算法相比,该技术能够在高到中等信噪比(SNR)下对更高额定PSK和QAM信号进行分类。对于相位抖动、残余载波或不完全均衡等信号损伤,该分类器已被证明具有相当的鲁棒性。本文介绍了应用的聚类算法,并给出了性能实例。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Identification of voiceband data signal constellations using a divisive cluster algorithm
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.
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