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Signal estimation-oriented reduced-rank channel estimation for MIMO communications

Conference Paper


Abstract


  • Signal estimation in MIMO communications typically suffers from performance degradations due to imperfect channel state information (CSI). Traditional robustification schemes rely on assumptions about the model uncertainty and may result in conservative performance. We introduce a rank-reduction approach that enhances the performance in training-based applications. A sequence of reduced-rank channel estimates are established from the training data. Multiple, distinct estimates of the transmit signal are then generated by applying standard detectors to each of those models, among which the 'best' is chosen by data-driven methods. This way significant performance improvements can be achieved, especially for ill-conditioned channels.

Publication Date


  • 2015

Citation


  • J. Tong, Q. Guo, S. Tong, J. Xi & Y. Yu, "Signal estimation-oriented reduced-rank channel estimation for MIMO communications," in Signal and Information Processing (ChinaSIP), 2015 IEEE China Summit and International Conference on, 2015, pp. 982-986.

Scopus Eid


  • 2-s2.0-84957606049

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/5639

Has Global Citation Frequency


Start Page


  • 982

End Page


  • 986

Place Of Publication


  • United States

Abstract


  • Signal estimation in MIMO communications typically suffers from performance degradations due to imperfect channel state information (CSI). Traditional robustification schemes rely on assumptions about the model uncertainty and may result in conservative performance. We introduce a rank-reduction approach that enhances the performance in training-based applications. A sequence of reduced-rank channel estimates are established from the training data. Multiple, distinct estimates of the transmit signal are then generated by applying standard detectors to each of those models, among which the 'best' is chosen by data-driven methods. This way significant performance improvements can be achieved, especially for ill-conditioned channels.

Publication Date


  • 2015

Citation


  • J. Tong, Q. Guo, S. Tong, J. Xi & Y. Yu, "Signal estimation-oriented reduced-rank channel estimation for MIMO communications," in Signal and Information Processing (ChinaSIP), 2015 IEEE China Summit and International Conference on, 2015, pp. 982-986.

Scopus Eid


  • 2-s2.0-84957606049

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/5639

Has Global Citation Frequency


Start Page


  • 982

End Page


  • 986

Place Of Publication


  • United States