LIAO Hong-shu, WEI Ping, LI Wan-chun. SNR Estimation Based on Finite Sample Data[J]. Journal of University of Electronic Science and Technology of China, 2012, 41(3): 364-367. DOI: 10.3969/j.issn.1001-0548.2012.03.007
Citation:
LIAO Hong-shu, WEI Ping, LI Wan-chun. SNR Estimation Based on Finite Sample Data[J]. Journal of University of Electronic Science and Technology of China, 2012, 41(3): 364-367. DOI: 10.3969/j.issn.1001-0548.2012.03.007
LIAO Hong-shu, WEI Ping, LI Wan-chun. SNR Estimation Based on Finite Sample Data[J]. Journal of University of Electronic Science and Technology of China, 2012, 41(3): 364-367. DOI: 10.3969/j.issn.1001-0548.2012.03.007
Citation:
LIAO Hong-shu, WEI Ping, LI Wan-chun. SNR Estimation Based on Finite Sample Data[J]. Journal of University of Electronic Science and Technology of China, 2012, 41(3): 364-367. DOI: 10.3969/j.issn.1001-0548.2012.03.007
This paper first demonstrats that signal subspace has finite dimensions from signal model. A conclusion is obtained by simulation test that both eigenvalues of signal subspace and noise subspace can't be evaluated precisely due to small size data. Then signal subspace dimensions are estimated accurately with Modified-AIC criterion using likelihood function depending only on noise space eigenvalues. A new robust SNR estimation method is proposed with the application of modified-AIC criterion. Regarding a variety of SNR and data size, simulation results show that the new method can be applied in lower SNR and shorter data samples environment.
XU Hai-bo, DU Huan, ZHANG Zhen-ren. Subspace Methods in OFDM Channel Estimation[J]. Journal of University of Electronic Science and Technology of China, 2006, 35(5): 752-754.
Wang Hong, Lü Youxin, Xiang Jingcheng. A New Subspace Pattern Recognition Method[J]. Journal of University of Electronic Science and Technology of China, 2004, 33(1): 5-8.
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