PROJECT TITLE :

On the Use of Extrinsic Probabilities in the Computation of Non-Bayesian Cramér–Rao Bounds for Coded Linearly Modulated Signal - 2018

ABSTRACT:

This contribution considers the non-Bayesian Cramér-Rao bound (CRB) related to parameter estimation from a linearly modulated signal observed in additive white Gaussian noise. We have a tendency to compare the precise CRB expression for coded modulation with 2 impromptu CRB (ACRB) expressions; the first ACRB is obtained by substituting in the precise CRB expression for uncoded modulation the a priori image possibilities by the extrinsic image possibilities; the second ACRB, that has received some attention in recent scientific publications, additionally assumes that the $64000 and imaginary elements of the symbols are freelance. Our exposition focuses on the particular case of part shift estimation. By means that of examples we show that though for some coded modulation schemes the precise and ACRBs yield just about the identical numerical result, for alternative coded modulation schemes the ACRBs differ considerably among themselves and from the exact CRB. We provide some explanations for this behavior. We have a tendency to also argue that both ACRBs are expected to virtually coincide with the precise CRB within the case of bit-interleaved coded modulation combined with an oblong constellations with independent in-part and quadrature mapping and a binary code for which the issue graph does not contain short cycles.