| Título | Cramér-Rao Bounds for SNR Estimation of Oversampled Linearly Modulated Signals |
| Tipo de publicación | Journal Article |
| Year of Publication | 2015 |
| Autores | López-Valcarce, R, Villares, J, Riba, J, Gappmair, W, Mosquera, C |
| Journal | IEEE Trans. Signal Processing |
| Volumen | 63 |
| Start Page | 1675 |
| Incidencia | 7 |
| Páginas | 1675-1683 |
| Date Published | 04/2015 |
| Palabras clave | adaptive signal processing, compass, Cramér-Rao bound (CRB), dynacs, oversampling, Signal-to-noise ratio (SNR) |
| Resumen | Most Signal-to-noise ratio (SNR) estimators use thereceiver matched filter output sampled at the symbol rate, anapproach which does not preserve all information in the analogwaveform due to aliasing. Thus, it is relevant to ask whetheravoiding aliasing could improve SNR estimation. To this end, wecompute the corresponding data-aided (DA) and non-data-aided(NDA) Cramér-Rao bounds (CRBs). We adopt a novel dual filterframework, which is shown to be information-preserving undersuitable conditions and considerably simplifies the analysis. It isshown that the CRB can be substantially reduced by exploitingany available excess bandwidth, depending on the modulationscheme, the SNR range, and the estimator (DA or NDA) type. |
| DOI | 10.1109/TSP.2015.2396013 |
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