一种非对称PCMA信号盲分离算法
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摘要
针对卫星通信中非对称成对载波多址(PCMA)信号的盲分离问题,提出一种基于同步挤压小波变换(SWT)的盲分离算法。该算法在混合多个信号前提下,首先按强信号进行同步,接着采用同步挤压小波变换提取时频曲线,最后去除混合信号中的噪声与强信号主频外的弱信号干扰,降低了强信号解调误码率。该算法具有在不具备协作通信方发送的信息序列的先验条件下,实现了非对称PCMA信号盲分离的特点。仿真结果表明,经本文算法处理后强信号解调误码性能比对混合信号直接硬判决时有较大提升。
Aiming at the problem of the blind source separation of the asymmetric paired carrier multiple access(PCMA), a blind separation algorithm based on the synchrosqueezing wavelet transform(SWT) is proposed. Under the premise of mixing multiple signals, the algorithm firstly synchronizes the mixed signal according to the strong signal, then extracts the time-frequency curve by using the SWT, and finally removes the noise and weak signal interference, which reduces the demodulation bit error rate of the signal. The algorithm achieves the blind separation of the asymmetric PCMA signal without the prior condition of the information sequence sent by cooperative communication. The simulation results show that the error performance of the strong signal demodulation after this algorithm is better than the direct hard decision of the mixed signal.
Aiming at the problem of the blind source separation of the asymmetric paired carrier multiple access(PCMA), a blind separation algorithm based on the synchrosqueezing wavelet transform(SWT) is proposed. Under the premise of mixing multiple signals, the algorithm firstly synchronizes the mixed signal according to the strong signal, then extracts the time-frequency curve by using the SWT, and finally removes the noise and weak signal interference, which reduces the demodulation bit error rate of the signal. The algorithm achieves the blind separation of the asymmetric PCMA signal without the prior condition of the information sequence sent by cooperative communication. The simulation results show that the error performance of the strong signal demodulation after this algorithm is better than the direct hard decision of the mixed signal.
引文
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[3] Tu S L,Zheng H,Gu N.Sigle-channel blind separation of two QPSK signals using per-survivor processing[C].IEEE Asia Pacific Conference on Circuits and Systems,Macao,China,Nov 30-Dec 3,2008.
[4] Yang Y,Peng H,Zhang D,et al.Markov chain monte carlo-based separation of paired carrier multiple access signals[J].IEEE Communications Letters,2016,20(11):2209-2212.
[5] 付迪,高勇.非对称PCMA卫星信号的截获方法[J].军事通信,2007(7):28-30,34.[ Fu Di,Gao Yong.Signal interception method for asymmetric PCMA satellite communication systems[J].Modern Electronics Technique,2007(7):28-30,34.]
[6] 黄强,彭华.基于非线性滤波的非对称PCMA信号盲分离[J].信号处理,2017,33(5):676-686.[Huang Qiang,Peng Hua.Blind separation of asymmetric PCMA signals based on nonlinear filtering[J].Journal of Signal Processing,2017,33(5):676-686.]
[7] 黄强,彭华,李天昀,等.基于软信息联合修正的非对称PCMA盲分离算法[J].通信学报,2017,38(4):178-189.[Huang Qiang,Peng Hua,Li Tian-yun,et al.Asymmetric PCMA blind separation algorithm based on joint soft information correction[J].Journal of Communications,2017,38(4):178-189.]
[8] 胡绍林,傅娜,郭文明.动态测量数据的高保真容错Q-滤波算法[J].宇航学报,2016,37(1):112-117.[Hu Shao-lin,Fu Na,Guo Wen-ming.High fidelity error tolerant Q-filtering algorithm for dynamic measurement data[J].Journal of Astronautics,2016,37(1):112-117.]
[9] 刘秀平,李小平,孙海峰.基于Daubechies小波的X射线脉冲星信号降噪研究[J].宇航学报,2012,33(12):1757-1761.[Liu Xiu-ping,Li Xiao-ping,Sun Hai-feng.Research on denoising of X ray pulsar signals based on Daubechies wavelet[J].Journal of Astronautics,2012,33(12):1757-1761.]
[10] 廖灿辉,周世东,朱中梁.从强信号掩盖中检出弱信号的一种新检测算法[J].系统仿真学报,2010(4):986-990.[Liao Can-hui,Zhou Shi-dong,Zhu Zhong-liang.A new detection algorithm for detection of weak signals from strong signal concealment[J].Journal of System Simulation,2010(4):986-990.]
[11] Daubechies I,Lu J,Wu H T.Synchrosqueezed wavelet transforms:a tool for empirical mode decomposition[J].Mathematics,2009.
[12] Anvari R,Siahsar M A N,Gholtashi S,et al.Seismic random noise attenuation using synchrosqueezed wavelet transform and low-rank signal matrix approximation[J].IEEE Transactions on Geoscience & Remote Sensing,2017,55(99):1-8.
[13] Mousavi S M,Langston C A,Horton S P.Automatic microseismic denoising and onset detection using the synchrosqueezed continuous wavelet transform[J].Geophysics,2016,81(4):341-355.
[14] Daubechies I,Lu J,Wu H T.Synchrosqueezed wavelet transforms:an empirical mode decomposition-like tool[J].Applied & Computational Harmonic Analysis,2011,30(2):243-261.
[15] 王振亚.单/多载波通信系统中同步算法研究及FPGA实现[D].西安:西安电子科技大学,2016.[Wang Zhen-ya.Research on synchronization algorithm in single/multicarrier communication system and FPGA implementation[D].Xi’an:Xi’an Electronic and Science University,2016.]
[16] Thakur G,Brevdo E,Fuckar NS,et al.The synchrosqueezing algorithm for time-varying spectral analysis:robustness properties and new paleoclimate applications[J].Signal Processing,2013,93(5):1079-1094.
[17] Proakis J G.数字通信(第五版)[M].张力军,译.北京:电子工业出版社,2011.