The fundamental detection problem in fading channels involves the correct estimation of transmitted symbols at the receiver in the presence of Additive White Gaussian Noise (AWGN). Detection can be considered when the receiver is assumed not to know the channel (non-coherent detection), or alternatively, when the random channel is tracked at the receiver (coherent detection). It can be shown that for a given error probability, coherent detection schemes require a Signal to Noise Ratio (SNR) that is 3dB less than the SNR required for non-coherent detection schemes. It is also known that the performance of coherent detection schemes can be further improved using space-frequency diversity techniques, for example, when multiple-input multiple-output (MIMO) antenna technologies are employed in conjunction with Orthogonal Frequency Division Multiplexing (OFDM). However, the superior performance promised by the MIMO-OFDM technology relies on the availability of accurate Channel State Information (CSI) at the receiver. In the literature, the Mean Square Error (MSE) performance of MIMO-OFDM CSI estimators is known to be limited by the SNR. This thesis adopts a di®erent view to estimator performance, by evaluating the accuracy of CSI estimates as limited by the maximum delay spread of the multipath channel. These considerations are particularly warranted for high data rate multi-user MIMO-OFDM systems which deploy large numbers of transmit antennas at either end of the wireless link. In fact, overloaded multi-user CSI estimation can be e®ectively studied by considering the grouping together of the user antennas for the uplink while conversely, considering a small number of antennas due to size constraints for the downlink. Therefore, most of the work developed in this thesis is concerned with improving existing single-user MIMO-OFDM CSI estimators but the results can be extended to multi-user system.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:494882 |
| Date | January 2008 |
| Creators | Mung'au, Franklin |
| Publisher | University of Hull |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://hydra.hull.ac.uk/resources/hull:996 |
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