Training-based Bayesian MIMO channel and channel norm estimation
2009 (English)In: 2009 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOLS 1- 8, PROCEEDINGS, IEEE , 2009, 2701-2704 p.Conference paper (Refereed)
Training-based estimation of channel state information in multi-antenna systems is analyzed herein. Closed-form expressions for the general Bayesian minimum mean square error (MMSE) estimators of the channel matrix and the squared channel norm are derived in a Rayleigh fading environment with known statistics at the receiver side. When the second-order channel statistics are available also at the transmitter, this information can be exploited in the training sequence design to improve the performance. Herein, mean square error (MSE) minimizing training sequences are considered. The structure of the general solution is developed, with explicit expressions at high and low SNRs and in the special case of uncorrelated receive antennas. The optimal length of the training sequence is equal or smaller than the number of transmit antennas.
Place, publisher, year, edition, pages
IEEE , 2009. 2701-2704 p.
, International Conference on Acoustics Speech and Signal Processing (ICASSP), ISSN 1520-6149
Channel matrix, Squared Frobenius norm, MMSE estimation, Rayleigh fading, Training optimization
IdentifiersURN: urn:nbn:se:kth:diva-30713DOI: 10.1109/ICASSP.2009.4960180ISI: 000268919201215ScopusID: 2-s2.0-70349195930ISBN: 978-1-4244-2353-8OAI: oai:DiVA.org:kth-30713DiVA: diva2:402722
IEEE International Conference on Acoustics, Speech and Signal Processing, Taipei, TAIWAN, APR 19-24, 2009
© 2009 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
QC 201103092011-10-262011-03-042012-01-23Bibliographically approved