TY - JOUR
T1 - Cramér-Rao Bounds for SNR Estimation of Oversampled Linearly Modulated Signals
JF - IEEE Trans. Signal Processing
Y1 - 2015
A1 - R. López-Valcarce
A1 - J. Villares
A1 - J. Riba
A1 - W. Gappmair
A1 - C. Mosquera
KW - adaptive signal processing
KW - compass
KW - Cramér-Rao bound (CRB)
KW - dynacs
KW - oversampling
KW - Signal-to-noise ratio (SNR)
AB -
Most Signal-to-noise ratio (SNR) estimators use the
receiver matched filter output sampled at the symbol rate, an
approach which does not preserve all information in the analog
waveform due to aliasing. Thus, it is relevant to ask whether
avoiding aliasing could improve SNR estimation. To this end, we
compute the corresponding data-aided (DA) and non-data-aided
(NDA) Cramér-Rao bounds (CRBs). We adopt a novel dual filter
framework, which is shown to be information-preserving under
suitable conditions and considerably simplifies the analysis. It is
shown that the CRB can be substantially reduced by exploiting
any available excess bandwidth, depending on the modulation
scheme, the SNR range, and the estimator (DA or NDA) type.
VL - 63
IS - 7
ER -