ITR/SY + SI (C-CR) Collaborative Research: Signal Processing and Channel Modelling in Low-Dimensional Subspaces for Wireless Communication in Multi-Antenna Systems

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ITR Small Proposal 0112508/ 0112573Friedlander/ScharfTitle: Signal Processing and Channel Modelling in Low-DimensionalSubspaces for Wireless Communication in Multi-Antenna SystemsAbstractThe problem of communicating information between a fixed basestation and many mobile peripherals dominates much of current research in wireless communication. The problem is tecnologically challenging because the channel that connects the basestation to the peripherals is random and time-varying. The most general solution requires space-time coding and signal processing that is "matched" to the channel. The objective of this research program is to extend the theory of space-time array processing (STAP) developed for radar applications, to multi-antenna wireless communication over fading channnels, in order to determine whenand how channel structure can be exploited for space-time signal processing gain and/or diversity. Theoretically, the results of this research advance the understanding of multi-antenna wireless communication between antenna arrays. Practically, they suggest methods for adaptively communicating between fixed basestations and mobiles and between fixed computers and movable storage area networks.Prior results by the principal investigators suggest that only the span of a low-dimensional channel subspace, and not the detailed physics of its coordinate representation, is required for the design of signals that optimize transmit diversity, and tranceivers that optimize the trade off between space-time processing gain and diversity. Moreover, the optimum transceiver statistics are just estimators of output signal-to-interference plus noise ratio (SINR), suggesting that transceiver statistics for decoding data can be used to estimate and track output SINR and network capacity. This means power and bandwidth may be adaptively allocated, using only transceiver statistics. So, in broad outline, this program is addressed to space-time channel modelling, using subspace methods; subspace signal and transceiver design for gain and diversity; and estimation of network capacity, using only transceiver statistics.