Estimation of the received signal amplitude is critical to the optimization of the performance of detectors for data communication systems operating in the presence of impulse-like interference. A binary data communication system in the presence of Laplace noise is considered. Maximum likelihood estimators are derived for both data-aided and non- data-aided cases. A ML-based non-data-aided absolute median estimator with simpler implementation is also proposed. The performances of the proposed estimators are examined and compared to the well-known mean estimator and absolute moment estimator in terms of their mean- squared errors. Numerical results quantify the superiority of the optimal ML estimators over the conventional estimators.
['Norman C. Beaulieu', 'Sijing Jiang']
ML Estimation of Signal Amplitude in Laplace Noise