UC San Diego

This dissertation aims to explore and analyze novel schemes for bandwidth efficient channel estimation in multiple-input multiple-output (MIMO) wireless systems. As the number of receive/transmit antennas increases in MIMO systems, the number of channel coefficients to be estimated increases. This, together with the low SNR of operation in MIMO systems, necessitates an increase in the pilot symbol overhead which leads to a reduction in the bandwidth efficiency. To alleviate this problem, we study several procedures such as whitening-rotation and superimposed pilots for bandwidth efficient MIMO channel estimation. The CRLB serves as an important tool in the performance evaluation of estimators which arise frequently in the fields of communications and signal processing. In applications such as semi-blind channel estimation one is frequently faced with the estimation of constrained complex parameters. We present a result for the Cramer-Rao bound (CRB) for complex-constrained parameters and the utility of this framework is illustrated in the subsequent work on semi-blind channel estimation. In addition to using the pilot sequence, the accuracy of the channel estimate at the receiver can be enhanced by employing second-order statistical information. For this purpose, we propose a whitening- rotation (WR) based algorithm for semi-blind estimation of the complex flat-fading MIMO channel matrix $H$. Utilizing complex constrained CRB, we show that the semi-blind scheme can significantly improve estimation accuracy. Next, we consider the problem of semi-blind (SB) channel estimation for multiple-input multiple-output (MIMO) frequency-selective (FS) channels. We motivate a Fisher information matrix (FIM) based analysis of this semi-blind estimation problem and demonstrate that the rank deficiency of the FIM is related to the number of un- identifiable parameters. We also establish the minimum number of pilot symbols necessary to achieve regularity (full-rank) of the FIM for identifiability. The efficacy and applicability of the semi-blind philosophy is further exemplified by demonstrating its utility in the context of channel estimation for MIMO systems employing Maximum Ratio Transmission (MRT). Superimposed pilots (SP) are another interesting alternative to reduce the impact of a pilot overhead without a significant increase in computational complexity. We present a study of the mean- squared error (MSE) and throughput performance of superimposed pilots (SP) for the estimation of a MIMO wireless channel. We illustrate a semi-blind scheme for SP based MIMO channel estimation, which improves performance over the traditional mean-estimator. A new result is presented for the worst-case capacity of a communication channel with correlated information symbols and noise. We also address the issue of optimal source-pilot power allocation for SP. In the end we consider the problem of estimation of a time-selective MIMO wireless channel using superimposed pilot (SP) symbols. We demonstrate a scheme for channel estimation based on a complex exponential basis expansion model (CEBEM) approximation of the time- selective wireless channel. We further reduce the MSE of estimation by employing an expectation-maximization (EM) based iterative estimation procedure