Antenna and algorithm design in MIMO communication systems: exploiting the spatial selectivity of wireless channels

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Forenza, Antonio

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Cellular telephony and wireless Internet access are creating a growing demand for high quality wireless communications. Unfortunately, the current wireless communication infrastructure is not fully equipped to offer these unprecedented data rates and quality of service. The major obstacles include limited bandwidth availability, limited transmit power, and fluctuations in signal strength which are intrinsic to the wireless channel. Future wireless standards are relying on innovative core technologies such as multiple-input multiple-output (MIMO) communications to overcome these problems. The spatial dimension due to antenna arrays at the transmitter and receiver of MIMO communication systems can be exploited by sophisticated signal processing techniques to offer high link capacity, enhanced resistance to interference, and robustness to channel fading. The benefits of MIMO technology are obtained through a combination of antenna arrays that can provide spatial diversity and algorithms that can adapt to the propagation channel. Antenna arrays have to be designed to be robust in different propagation scenarios and provide the degrees of spatial diversity expected by the algorithms. The algorithms can adaptively reconfigure the transmission methods by tracking the changing channel conditions. The premise of the work presented in this dissertation is that antenna arrays and algorithms at the physical layer can be designed, based on performance metrics from different layers, to exploit the channel spatial selectivity, resulting in improved system performance. This dissertation presents performance analysis and design methodology of MIMO arrays, employing pattern diversity technique, in spatially correlated channels. The proposed array designs consist of collocated circular patch antennas, or circular patch arrays (CPAs). The benefit of pattern diversity, obtained through CPAs, over conventional space diversity technique is first demonstrated through analysis. Then a novel design methodology for compact MIMO arrays optimized with respect to microwave theory and communication theoretic metrics for given size constraints is proposed. This dissertation also presents adaptive algorithms at the physical layer to switch between different MIMO transmission schemes, based on statistical channel information. These adaptive algorithms exploit the spatial selectivity inherent in the channel and are designed to enhance the spectral efficiency of next generation wireless systems, for predefined target error rate.