Exploiting the Cramér-Rao bound for optimised sampling and quantisation of FRI signals

This contribution considers the sampling process for Finite Rate of Innovation signals including quantisation errors and additive white Gaussian noise. For some applications the total amount of bits available for the sampling process is constrained, e.g. due to memory limitations. Thus, the sharing of these bits between sampling rate and the quantisation accuracy has to be optimised. In particular, the Cramér-Rao bound is determined and the bit allocation is optimised w.r.t. the CRB. Finally, the analytical results are compared with simulation results obtained by spectral estimation methods.