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Autocorrelation Based SNR Estimation

Signal-to-noise ratio (SNR) estimation is one of the important research topics in wireless
communications. In the receiver, many algorithms require SNR information to achieve optimal performance. In this thesis, an autocorrelation based SNR estimator is proposed. The proposed method utilizes the correlation properties of symbol sequence and the uncorrelated properties of noise sequence to distinguish the signal power from the received signal. Curve fitting method is used for SNR estimator to predict the signal power.
Mean and variance performance of the proposed SNR estimator is compared with that of the conventional SNR estimator by computer simulations. These simulations consider additive white Gaussian noise and multipath Rayleigh fading channel with BPSK, 8PSK, 16QAM and 64QAM modulation schemes. According to the simulation results, the proposed method can provide better performance than conventional methods in both mean and mean-square-error.

Identiferoai:union.ndltd.org:NSYSU/oai:NSYSU:etd-1015107-212628
Date15 October 2007
CreatorsHuang, Yao-pseng
ContributorsMing-Der Shieh, Ju-Ya Chen, Ching-Piao Hung, Jieh-Chian Wu, Chin-Der Wann
PublisherNSYSU
Source SetsNSYSU Electronic Thesis and Dissertation Archive
LanguageCholon
Detected LanguageEnglish
Typetext
Formatapplication/pdf
Sourcehttp://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-1015107-212628
Rightsnot_available, Copyright information available at source archive

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