Space-time processing : an experimental test platform and algorithms.

This Thesis describes the concept, architecture, development and demonstration of a Smart Antenna Software Radio Test System (SASRATS). SASRATS was designed and developed as a functional and flexible system to facilitate the field testing of space-time processing architectures and algorithms. It is designed to facilitate the correlation of theoretical, simulated and measured performance. The SASRATS architecture has the capability of batch, pseudo-real and real time implementation of signal processing algorithms. It is used here to verify the work done by the author and others in the field of signal enumeration and blind beamforming. The Thesis develops a robust method to enumerate the incident signals impinging on a uniform but variable size linear array independent of the extent of their correlation in a Rayleigh flat fading channel environment. The method self-optimizes the array size by minimizing the number of antennas with respect to the number of signals and adapts continuously to maintain optimum performance in a mobile environment where users (signals) come and go. An algorithm is formulated with simulation and field results presented. A robust channel order estimation algorithm using multiple antennas is also presented. We show that the approach has better performance than the conventional information theoretic based channel order estimation algorithms. It operates over a wide range of signal-to-noise ratios and is tolerant to correlation between channels. Algorithm performance is evaluated via computer simulation