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采用SRM准则的盲均衡器

DOI: 10.13190/jbupt.200804.6.019, PP. 6-9

Keywords: 均衡器,盲均衡,结构风险最小化,特征恢复

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Abstract:

提出了一种新的采用结构风险最小化(SRM)准则的盲均衡器(SRM-BE)。该方法根据信号的特征恢复思想,以SRM为准则构造具有时间去相关特性的代价函数,采用静态迭代学习算法在线跟踪信道。通过仿真实验,并与采用最小均方误差准则的盲均衡器(LMS-BE)和采用神经网络的盲均衡器(NN-BE)进行比较,结果表明该方法的非线性均衡性能最佳。

References

[1]  Sato Y. A method of self-recovering equalization for multilevel amplitude modulation systems[J]. IEEE Trans on Communications, 1975, 23(6): 679-682.
[2]  Godard D. Self-recovering equalization and carrier-tracking in two-dimensional data communication system[J]. IEEE Trans on Communications, 1980, 28(12): 1867-1875.
[3]  Giannakis G B, Mendel J. Identification of non-minimum phase systems using higher-order statistics[J]. IEEE Trans on ASSP, 1989, 37(3): 360-377.
[4]  Zhou Y, Leung H, Yip P, et al. Blind identification of multi-channel FIR systems based on linear prediction[J]. IEEE Trans on Signal Processing, 2000, 48(9): 214-218.
[5]  Fang Yangwang, Jiao Licheng, Zhang Xianda, et al. On the convergence of volterra filter equalizers using a Pth-order inverse approach[J]. IEEE Trans on SP, 2001, 49(8): 1734-1744.
[6]  梁启联, 周正. 基于多层神经网络的盲均衡算法[J]. 北京邮电大学学报, 1996, 19(3): 27-32. Liang Qilian, Zhou Zheng. Blind equalization based on multilayer neural network[J]. Journal of Beijing University of Posts and Telecommunications, 1996, 19(3): 27-32.
[7]  Vapnik V N. 统计学习理论的本质[M]. 张学工, 译. 北京: 清华大学出版社, 2000: 63-68.
[8]  Liu R W, Dong Guojie. A fundamental theorem for multiple-channel blind equalization[J]. IEEE Trans on Circuits and Systems-Ⅰ: Fundamental Theory and Applications, 1997, 44(5): 472-473.
[9]  刘郁林. 无线通信中对时变色散信道的盲均衡与盲辨识方法研究. 成都: 电子科技大学通信与信息工程学院, 2002.
[10]  Haykin S. Adaptive filter theory [M]. 4th ed. Pearson Education Inc, 2002: 637-641.

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