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.
The generation and behavior of the fractal Koch array factor from a Kaiser window generator is studied. The main advantage of using Kaiser windows is that pattern parameters become much more flexible through altering the Kaiser window. The mainlobe width, current distribution, side-lobe ratio are now adjustable. Different reduced array structures can be obtained by using different threshold levels. Higher threshold values result in a highly reduced number of elements but they may highly distort the pattern and, hence, the multiband behavior. Finally, we study the effect of quantization of the feeding values. Quantization is necessary for implementation and simplification purposes. Several configurations of current distributions with the corresponding patterns are illustrated for different quantization levels. It is shown that moderate quantization keeps the same interesting similarity properties at several bands.