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A robust MISO training sequence design
KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
Southeast University, Nanjing. (Communications Research Lab.)
KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0002-3599-5584
2013 (English)In: 2013 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), New York: IEEE , 2013, 4564-4568 p.Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, the problem of robust training sequence design for multiple-input single-output (MISO) channel estimation is investigated. The mean-squared error (MSE) of the channel estimates is considered as a performance criterion to design an optimized training sequence which is a function of channel covariance matrix. In practice, the channel covariance matrix is not perfectly known at the transmitter side. Our goal is to take such imperfection into account and propose a robust design following the worst-case philosophy which results in finding the optimal training sequences for the least favorable channel covariance matrix within a deterministic uncertainty set. In this work, we address the formulated minimax design problem under different assumptions of the uncertainty set, and we show that for a unitarily-invariant uncertainty set, the optimally robust training sequence shares its eigenvectors with the channel covariance matrix. Furthermore, we give analytical closed-form solutions for robust training sequences if the spectral norm or nuclear norm are considered as constraints to bound the existing uncertainty.

Place, publisher, year, edition, pages
New York: IEEE , 2013. 4564-4568 p.
Series
ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, ISSN 1520-6149
Keyword [en]
Robust training sequences, worst-case robustness, unitarily-invariant uncertainty set, imperfect covariance, MIMO channel estimation
National Category
Signal Processing Telecommunications
Identifiers
URN: urn:nbn:se:kth:diva-133207DOI: 10.1109/ICASSP.2013.6638524ISI: 000329611504145Scopus ID: 2-s2.0-84890505448ISBN: 978-147990356-6 (print)OAI: oai:DiVA.org:kth-133207DiVA: diva2:659929
Conference
2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013; Vancouver, BC; Canada; 26 May 2013 through 31 May 2013
Note

QC 20140225

Available from: 2013-10-28 Created: 2013-10-28 Last updated: 2014-02-25Bibliographically approved

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Bengtsson, Mats

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CiteExportLink to record
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Citation style
  • apa
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