Efficient Modelling and Performance Analysis of Wideband Communication Receivers

This thesis deals with Symbol Error Rate (SER)-simulation of wireless communications and its application into throughput analysis of UltraWideband (UWB) systems. The SERs will be simulated in C++ using the Monte Carlo method and when some are calculated, the rest will be estimated using a novel extrapolation method. These SER values will be very accurate and in this thesis go as low as 1.0e-14. Reaching that low values would otherwise be impossible using the traditional Monte Carlo method, because of very large computation time. However, the novel extrapolation method, can simulate a SER-curve in less than 30 seconds. It is assumed that the noise belongs to the Generalized Gaussian distribution family and among them noise from the Normal distribution (Gaussian noise) gives the best result. It is to be noted that Gaussian noise is the most commonly used in digital communication simulations. Although the program is used for throughput analysis of UWB, the program could easily be adapted to various signals. In this thesis, throughput analysis means a plot with symbol rate vs distance. From any given symbols, the user can, with a desired minimum SER, generate an extrapolated SER-curve and see what symbol rate can be achieved by the system, while obeying power constraints of signals imposed by international laws. The developed program is, by comparing with published theoretical results, tested for QAM and PSK cases, but can easily be extended to UWB systems