Importance sampling evaluation of digital phase detectors based on extended Kalman-Bucy filters

This paper proposes an importance sampling methodology for the performance evaluation of a class of open-loop receivers with random carrier phase tracking in additive white Gaussian noise channels. The receivers, consisting of a bank of extended Kalman-Bucy filters and a decision algorithm based on the filters’ innovations processes, perform symbol-by-symbol phase detection while kepping track of the random phase process within the symbol interval. We use a large deviations approach to start a stochastic importance sampling optimization, both for the irreducible error floor and for the general noisy operation of the receiver. Our simulations show a practical coincidence with conventional Monte Carlo results, with considerable simulation time gains.