一种新的基于改进PASTd的中频信号盲信噪比估计算法

隋丹; 葛临东

doi:10.3724/SP.J.1146.2006.00645

一种新的基于改进PASTd的中频信号盲信噪比估计算法

doi: 10.3724/SP.J.1146.2006.00645

隋丹,
葛临东

基金项目:

国家部级基金资助课题

计量
- 文章访问数: 3307
- HTML全文浏览量: 95
- PDF下载量: 729
- 被引次数: 0
出版历程
- 收稿日期: 2006-05-15
- 修回日期: 2006-10-08
- 刊出日期: 2007-07-19

A Novel Blind SNR Estimator Based on the Modified PASTd Algorithm for IF Signals

摘要

摘要: 该文提出一种加性高斯白噪声信道下基于改进的紧缩投影近似子空间跟踪(PASTd)的中频信号盲信噪比估计算法。将Gram-Schmidt正交化过程引入到PASTd中，使计算得到的特征向量相互正交，从而保证算法具有更好的收敛性能。对MPSK(M=2,4,8)信号和MQAM(M=16,64,128,256)信号进行了大量计算机仿真，结果表明该算法性能稳定，并且当信噪比变化范围为5dB到25dB时，所得到的估计偏差小于1dB，估计标准差在0.3以内。与基于特征值分解的算法相比，能够在得到精确估计结果的同时，大大减小运算复杂度。
- 信噪比估计;盲算法;中频信号;PASTd
Abstract: A blind Signal-to-Noise Ratio (SNR) estimator based on the modified PASTd (Projection Approximation Subspace Tracking deflation) algorithm is proposed in this paper for Intermediate Frequency (IF) signals in the Additive White Gaussian Noise (AWGN) channel. The orthogonality of the estimated eigenvectors is guaranteed by the use of the modified Gram-Schmidt orthogonization process in the original PASTd method. Computer simulations are performed for the commonly used IF signals, such as MPSK (M=2,4,8) and MQAM (M=16,64,128,256) signals. The results show that the performance of the algorithm is robust and when the true SNR is in the range from 5dB to 25dB the estimation bias is under 1dB and the corresponding STD is within 0.3. Compared with the Eigenvalue Decomposition (ED)-based method, the proposed algorithm can achieve a more accurate estimation with a simple computational complexity.

HTML全文

参考文献(1)

Li B, DiFazio R, and Zeira A. A low bias algorithm to estimate negative SNRs in an AWGN channel[J].IEEE Comm. Letters.2002, 6(11):469-471[5]Wiesel A, Goldberg J, and Messer H. Non-data-aided Signal-to-Noise-Ratio estimation. Proc. IEEE ICC2002, New York, 2002: 197-201.[6]Matzner R and Englberger F. An SNR algorithm using fourth-order moments. Proc. IEEE Int. Symp. Information Theory, Trondheim, Norway, 1994: 119.[7]Shah B. The split symbol moments SNR estimator in narrow-band channels[J].IEEE Trans. on Aerospace and Electronic Systems.1990, 26(5):737-747[8]詹亚锋, 曹志刚, 马正新. 无线数字通信的盲信噪比估计. 清华大学学报(自然科学版), 2003, 43(7): 957-960. Zhan Ya-feng, Cao Zhi-gang, and Ma Zheng-xin. Blind SNR estimates in wireless digital communications[J].Journal of Tsinghua Univeristy(Science Technology.2003, 43(7):957-960[9]范海波, 陈军, 曹志刚. AWGN信道中非恒包络信号SNR估计算法. 电子学报, 2002, 30(9): 1369-1371. Fan Hai-bo, Chen Jun, and Cao Zhi-gang. An algorithm of SNR estimation for non-constant envelope signal in the AWGN channel. Acta Electronica Sinica, 2002, 30(9): 1369-137.

Pauluzzi D R and Beaulieu N C. A comparison of SNR estimation techniques for the AWGN channel[J].IEEE Trans. on Communications.2000, 48(10):1681-1691[2]Summers T A and Wilson S G. SNR mismatch and online estimation in Turbo decoding[J].IEEE Trans. on Communications.1998, 46(4):421-423[3]许华, 郑辉. MPSK信号的最大似然SNR估计方法[J].电子与信息学报.2005, 27(4):527-531. Xu Hua and Zheng Hui. On the maximum-likelihood SNR estimation algorithm for MPSK signals[J].Journal of Electronics Information Technology.2005, 27(4):527-531.

施引文献

资源附件(0)

访问统计