A study on SNR estimation algorithms for channel state estimation in Communication Satellite Systems employing Fade Mitigation Techniques
Channel state estimation is one of the key processes carried out at the physical layer of Satellite Systems employing Fade Mitigation Techniques such as Adaptive Coding and Modulation ACM. An accurate and reliable channel estimate is needed to fully realize the capacity gains accrued by using ACM. In this paper the SNR estimation algorithms, which perform the role of channel state estimators, are analysed from a system point of view to get a quantitative idea on the number of received symbols needed to get a reliable estimate, and the impact of interference noise on it. A DVB type satellite system has been investigated for the study. An improvement over the Maximum Likelihood ML estimator using Bayesian principles is suggested and illustrated.
Rapid transfer alignment has strict demands for filtering accuracy and convergent velocity,but alignment accuracy is seriously degraded if there exist outliers in measurements.A novel approach to reject outliers is proposed,a small sequence sampled online makes up of a new sequence by forward symmetry extension,which is processed by wavelet threshold de-noising,then outliers can be detected,new measurements made up of previous measurements act as current inputs of Kalman filter,the degradation caused by outlier is removed,accuracy of filtering system obtained for the demand of transfer alignment.