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低信噪比数字通信信号识别算法研究
引用本文:杨伟超,张忠,丁群.低信噪比数字通信信号识别算法研究[J].通信技术,2009,42(1):68-70.
作者姓名:杨伟超  张忠  丁群
作者单位:黑龙江大学电子工程学院,黑龙江,哈尔滨,150080
基金项目:黑龙江省教育厅重点项目,黑龙江省高校重点试验室(黑龙江大学)资助项目
摘    要:基于高阶累积量可以抑制高斯噪声的特性以及分形盒维数对噪声不敏感的特性,对于现代通信中常用的BPSK、QPSK、OQPSK、MSK和GMSK五种信号,建立了信号模型。理论推导了信号的高阶累积量特征,分析了信号的分形盒维数特征,提出了一种有效的识别算法。仿真试验证实了算法的可行性。

关 键 词:高阶累积量  分形维数  调制识别  特征参数

Algorithms for Modulation Recognition of Digital Communication Signals at Low SNR
YANG Wei-chao,ZHANG Zhong,DING Qun.Algorithms for Modulation Recognition of Digital Communication Signals at Low SNR[J].Communications Technology,2009,42(1):68-70.
Authors:YANG Wei-chao  ZHANG Zhong  DING Qun
Institution:(Department of Electronic Engineering, Heilongjiang University, Harbin Helongjiang 150080, China)
Abstract:Higher-order cumulants can suppress Gaussian noise and the fractal dimension is not sensitive to noise. For BPSK, OPSK, OOPSK, MSK and GMSK signals, which are frequently used in modern communication, signal models are constructed, the higher-order cumulant characteristics of signals theoretically deduced, and fractal box dimension characteristics of signals analyzed. Finally, a valid signal recognition algorithm is proposed, and the simulation proves the feasibility of the algorithm.
Keywords:higher-order cumulants: fractal dimension: modulation recognition: feature parameter
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