MIMO wireless systems with limited channel state information at the transmitter
Multiple input multiple output (MIMO) systems using multiple transmit and receive antennas are widely recognized as an effective means to significantly improve the spectral efficiency and wireless link reliability. The performance of a MIMO system can be further enhanced when channel knowledge can b...
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| Médium: | Dissertation |
| Jazyk: | angličtina |
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ProQuest Dissertations & Theses
01.01.2008
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| ISBN: | 0549930442, 9780549930440 |
| On-line přístup: | Získat plný text |
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| Shrnutí: | Multiple input multiple output (MIMO) systems using multiple transmit and receive antennas are widely recognized as an effective means to significantly improve the spectral efficiency and wireless link reliability. The performance of a MIMO system can be further enhanced when channel knowledge can be made available at the transmitter. Maximum gain can be achieved when perfect channel knowledge is available. In practice, however, perfect channel knowledge at the transmitter is never available because of the time varying nature of the channel and due to unavoidable estimation errors. As a result, the available channel state information at the transmitter (CSIT) is usually outdated instantaneous and/or statistical in nature. Precoding is a transmitter processing technique that exploits CSIT. A linear precoder functions as a multimode beamformer that spatially directs the signal in orthogonal directions and allocates power based on the available channel knowledge. The main objective of this thesis is to design robust precoding schemes when limited channel state information is available at the transmitter. Throughout the thesis, perfect channel knowledge is assumed at the receiver. Our first contribution is a performance analysis for the decorrelator, minimum mean squared error and successive interference cancelation receivers for precoded systems under various degrees of CSIT. We show that significant performance gain can be achieved by precoding even with only a moderate amount of correlation between the available imperfect channel estimate and the current channel. Next, we address the case when channel covariance information alone is available at the transmitter. The precoder spatially directs the signal based on the covariance information. Using results for random matrix theory, we propose novel iterative power allocation algorithms that maximize the spectral efficiency. We proceed to analyze the more general case when both the channel mean and covariance information is available at the transmitter. For the MIMO system with decorrelator receiver, we approximate the SNR of each spatial stream by a standard noncentral Chi-squared random variable. Using the moments of the SNR of each subchannel, we obtain a Taylor series approximation for the total average capacity. The obtained approximation is used to design a linear precoder that maximizes the average capacity of the system. Finally, we present a novel linear precoder design for general space-time block coded (STBC) MIMO systems when both the channel mean and covariance information is available at the transmitter. The linear precoder is designed via approximate joint diagonalization of the channel mean and transmit covariance matrices. The resulting precoder minimizes the Chernoff bound on the pair-wise error probability between a pair of block code words, averaged over channel fading statistics. |
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| Bibliografie: | SourceType-Dissertations & Theses-1 ObjectType-Dissertation/Thesis-1 content type line 12 |
| ISBN: | 0549930442 9780549930440 |