Title :
On the Blind SNR Estimation for IF Signals
Author :
Sui Dan ; Lindong, Ge
Author_Institution :
Inf. Eng., Zhengzhou Univ., Henan
fDate :
Aug. 30 2006-Sept. 1 2006
Abstract :
Signal-to-noise ratio (SNR) is a widely used significant parameter in communication systems. An eigenvector decomposition and subspace approach is employed for the blind SNR estimation for intermediate frequency (IF) signals in additive white Gaussian noise (AWGN) channel. The signal subspace dimension is determined by the eigenvector decomposition of the sample correlation matrix of the received signals and the minimum description length (MDL) criteria. Then the estimated SNR can be obtained by the computation of the power of the desired signal and the noise, respectively. The proposed algorithm requires no information on the modulation scheme and the parameters of the received signals. Computer simulations are performed for commonly used IF signals, such as MPSK, MFSK and MQAM. The results show that when the true SNR varies from -5dB to 20dB the estimation bias is within 0.6dB and the corresponding standard deviation (STD) is under 0.55
Keywords :
AWGN channels; blind source separation; channel estimation; eigenvalues and eigenfunctions; matrix algebra; AWGN channel; IF signal; MDL criteria; MFSK; MPSK; MQAM; additive white Gaussian noise; blind SNR estimation; communication system; computer simulation; correlation matrix; eigenvector decomposition; intermediate frequency signal; minimum description length; signal-to-noise ratio; standard deviation; AWGN; Additive white noise; Amplitude estimation; Computer simulation; Frequency estimation; Gaussian noise; Maximum likelihood estimation; Polynomials; Signal to noise ratio; Statistics;
Conference_Titel :
Innovative Computing, Information and Control, 2006. ICICIC '06. First International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7695-2616-0
DOI :
10.1109/ICICIC.2006.323
