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An approximate maximum likelihood estimator for SNR jointly using pilot and data symbols

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2 Author(s)
Yunfei Chen ; Dept. of Electr. & Comput. Eng., Alberta Univ., Edmonton, Alta., Canada ; Beaulieu, N.C.

A novel maximum likelihood-based estimator for signal-to-noise ratio (SNR) is derived. Previous SNR estimators are mainly based on using either the pilot symbols or the data symbols. However, in a practical communication system, a frame usually consists of both pilot and data symbols. In this work, a new SNR estimator that uses all available symbols (pilot and data) in a frame is developed for binary phase shift keying signals. The performance of this estimator is examined. Numerical results are presented to show the potential improvement obtained by using this new estimator.

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Communications Letters, IEEE  (Volume:9 ,  Issue: 6 )