Interest in Ultra-wideband (UWB) has surged since the FCC's approval of a First Report and Order in February 2002 which provides spectrum for the use of UWB in various application areas. Because of the extremely large bandwidth UWB is currently being touted as a solution for high data rate, short-range wireless networks. An integral part of designing systems for this application or any application is an understanding of the statistical nature of the wireless UWB channel. This thesis presents statistical characterizations for the large and small scale indoor channel. Specifically, for large scale modeling channel frequency dependence is investigated in order to justify the application of traditional narrowband path loss models to UWB signals. Average delay statistics and their distributions are also presented for small scale channel modeling.

The thesis also investigates narrowband interference cancellation. To protect legacy narrowband systems the FCC requires any UWB transmission to maintain a very low power spectral density. However, a UWB system may therefore be hampered by the presence of a higher power narrowband signal. Narrowband interferers have a much greater power spectral density than UWB signals and can negatively affect signal acquisition, demodulation, and ultimately lead to poor bit error performance. It is therefore desirable to mitigate any in-band narrowband interference. If the interferer's frequency is known then it may simply be removed using a notched filter. It is however of more interest to develop an adaptive solution capable of canceling interference at any frequency across the band. Solutions which are applied in the analog front end are preferable to digital backend solutions since the latter require extremely high rate sampling. The thesis therefore discusses two analog front-end interference cancellation techniques. The first technique digitally estimates the narrowband interference (this is possible because the UWB signal is not being sampled) and produces an RF estimate to perform the narrowband cancellation in the analog domain. Two estimation techniques, an LMS algorithm and a transversal filter, are compared according to their error performances. The second solution performs real-time Fourier analysis using transform domain processing. The signal is converted to the frequency domain using chirp Fourier transforms and filtered according to the UWB spectrum. This technique is also characterized in terms of bit error rate performance. Further discussion is provided on chirp filter bandwidths, center frequencies, and the applicability of the technology to UWB.