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基于矩方法和Kolmogorov-Smirnov检验的调制方式及信噪比联合估计 被引量:1

Joint Estimation of Modulation and SNR via Method of Moments and Kolmogorov-Smirnov Test
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摘要 提出了一种基于矩方法和Kolmogorov-Smirnov(K-S)检验的调制方式及信噪比联合估计算法。对给定的备选调制方式集,利用矩方法估计出接收信号对应各备选调制方式的信噪比,以此仿真出各调制方式对应的系列参考信号;基于K-S检验,将接收信号的经验累积分布同一系列参考信号的经验累积分布进行对比,找到与其最为接近的参考信号,该参考信号对应的调制方式和信噪比即为接收信号对应的估计结果。仿真表明,在低信噪比条件下,该算法能够对调制方式和信噪比进行有效的联合估计,计算复杂度较低,有一定的工程应用价值。 In this paper,we develop a novel non-data-aided(NDA) joint estimation algorithm of modulation format and signal-to-noise ratio(SNR) based on Kolmogorov-Smirnov(K-S) test and method of moments(MOM).For a given set of alternative modulation format,we can estimate the SNRs of the received signal corresponding to the different alternative modulation format based on the MOM and simulate a series of reference signals corresponding to each modulation format; then,based on the K-S test,the empirical cumulative distribution function(ECDF) of certain decision statistic derived from the received signal is computed and compared with pre-stored ECDFs of reference signals.Furthermore,the specific modulation format and SNR,with which the pre-stored ECDFs is the closest to the ECDF of the received signal,are selected as the estimates.We can obtain the estimates of modulation format and SNR simultaneously,which is a promising characteristic in many cases.Extensive simulation results demonstrate that the proposed joint estimator can obtain the estimates of modulation format and SNR value in the condition of lower SNR.The proposed joint estimator has lower computational complexity and a certain value in engineering.
出处 《信息工程大学学报》 2017年第4期399-402,408,共5页 Journal of Information Engineering University
关键词 调制方式及信噪比联合估计 矩方法 Kolmogorov-Smirnov检验 joint estimation of modulation and SNR method of moments Kolmogorov-Smirnov test
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  • 1Nandi A K, Azzouz E E. Automatic identification of digital mod ulation types[J]. Signal Processing, 1995,47(1) :55 - 69.
  • 2Azzouz E E, Nandi A K. Procedure for automatic recognition of analogue and digital modulations[J] IEE Proceedings Commu nications, 1996,143 (5): 259 - 266.
  • 3Hassan K, Dayoub I, Hamouda W, et al. Automatic modulation recognition using wavelet transform and neural networks in wireless systems[J]. EURASIP Journal on Advances in Signal Processing, 2010(42) : 1 - 13.
  • 4Mobasseri B G. Digital modulation classification using constella tion shape[J]. Signal Processing, 2000,80 (2) : 251 - 277.
  • 5Swami A, Sadlcr B M. Hierarchical digital modulation classification using cumulants[J]. IEEE Trans. on Communications, 2000,48(3):416 - 429.
  • 6Wong M L D, Nandi A K. Automatic digital modulation recognition using artificial neural network and genetic algorithm[J]. Signal Processing ,2004,84(2) :351 - 365.
  • 7Ebrahimzadeh A, Ranjbar A. Intelligent digital signal type identification[J]. Engineering Applications of Artificial Intelligence,2008,21(4) :569 - 577.
  • 8Guldemir H, Sengur A. Online modulation recognition of ana log communication signals using neural network [J]. Expert Systems with Applications, 2007, 33 (1) : 206 - 214.
  • 9Lin SW, Ying K C, Chen SC, et al. Particle swarm optirniza tion for parameter determination and feature selection of sup port vector machines[J].Expert Systems with Applications, 2008,35(4) :I817 - 1824.
  • 10Avci E, Avci D. Using combination of support vector machines for automatic analog modulation recognition[J]. Expert Sys terns with Applications, 2009,36 (2) : 3956 - 3964.

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