Joint Transmit and Receive Filter Optimization for Sub-Nyquist Delay-Doppler Estimation - 2018


In this Project, a framework is presented for the joint optimization of the analog transmit and receive filter with respect to a parameter estimation drawback. At the receiver, conventional signal processing systems limit the two-sided bandwidth of the analog prefilter B to the speed of the analog-to-digital converter fs to fits the well-known Nyquist-Shannon sampling theorem. In distinction, here we consider a transceiver that by design violates the common paradigm B = f s .To the current end, at the receiver, we permit for a better prefilter bandwidth B > f s and study the achievable parameter estimation accuracy underneath a mounted sampling rate when the transmit and receive filter are jointly optimized with respect to the Bayesian Cramer-Rao lower sure. For the case of delay-Doppler estimation, we have a tendency to propose to approximate the desired Fisher data matrix and solve the transceiver design downside by an alternating optimization algorithm. The presented approach allows us to explore the Pareto-optimal region spanned by transmit and receive filters that are favorable under a weighted mean squared error criterion. We tend to conjointly discuss the computational complexity of the obtained transceiver style by visualizing the ensuing ambiguity operate. Finally, we verify the performance of the optimized styles by Monte Carlo simulations of a probability-based estimator.

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