Space-time equalization in wireless systems with multiple transmit/receive array antennas

In the past two decades, wireless communications has experienced a tremendous growth. Therefore, techniques that can improve the spectral efficiency and enhance the wireless system performance are of great interest. Space-time processing techniques (known as Smart Antennas) have been introduced to overcome some of these challenges. The fundamental idea is to use multiple antennas combined with signal processing in both space and time, in order to improve the wireless system performance. The focus of this thesis is on mitigating the effect of the Inter-symbol Interference (ISI), for wireless systems with multiple transmit/receive antennas, also known as channel equalization.; A new estimation-based approach is proposed for implementing a spatio-temporal MMSE Decision Feedback Equalizer (DFE) for MIMO channels. Both finite-length and infinite-length MIMO Decision Feedback Equalizers are considered. For the infinite-length case the DFE problem leads to solving a matrix spectral factorization. We have proposed an estimation-based spectral factorization solution for the infinite-length MIMO DFE. The solution leads to a simple, recursive formulation for the MIMO DFE matrices. For the finite-length case the DFE problem leads to solving a corresponding Cholesky factorization. We have proposed an estimation-based approach that leads to a simple, recursive algorithm to perform the Cholesky factorization. We have exploited the structure of the DFE problem to reduce the complexity of the Cholesky factorization by an order of magnitude.; The thesis also investigates an estimation-based approach to adaptive spatio-temporal equalization. We consider both Linear and Decision Feedback equalizers. For the considered equalizers a least squares solutions is formulated, based on which recursive solutions using Riccati recursions are proposed. These solutions are tested by simulating the MIMO system. The effect of MIMO channel singularity on the system performance is also studied. The proposed solutions do not require channel identification and will also enable optimum equalizer adaptation and tracking of channel changes.; Finally in the last part of the thesis we have shown, how to combine space-time coding and transmit optimization to achieve significant coding gain. We show that when the channel has ISI, adaptive antennas utilizing an optimized transmit filter, can be combined with delay-diversity coding to achieve a diversity gain and a large coding gain.