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Stein, M.; Lenz, A.; Nossek, J. 
Optimum Analog Receive Filters for Detection and Inference Under a Sampling Rate Constraint 
The problem of optimum analog receive filtering for digital signal detection and parameter estimation is considered. Here the case of a signal source with bandwidth Bt and a receiver with fixed sampling rate fs is discussed under the assumption that 2Bt > fs. We investigate the impact of adjusting the receive bandwidth Br of the analog pre-filter, which is applied prior to the sampler, with respect to the deflection coefficient or the Fisher information measure. This reveals that the design rule 2Br < fs, known as the sampling theorem, does not necessarily lead to optimum system performance. Studying the two analytical information measures under a fix sampling rate fs and an arbitrary choice of Br, we provide an example where receive setups with 2Br > fs achieve higher detection and parameter estimation performance. 
Book / Congress title:
IEEE Int. Conf. Acoustic, Speech and Signal Processing (ICASSP)