NDLI: Training-based and semiblind channel estimation for MIMO systems with maximum ratio transmission (2006)

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Training-based and semiblind channel estimation for MIMO systems with maximum ratio transmission (2006)

Content Provider	CiteSeerX
Author	Murthy, Ra R. Jagannatham, Aditya K. Rao, Bhaskar D.
Abstract	Abstract—This paper is a comparative study of training-based and semiblind multiple-input multiple-output (MIMO) flat-fading channel estimation schemes when the transmitter employs max-imum ratio transmission (MRT). We present two competing schemes for estimating the transmit and receive beamforming vectors of the channel matrix: a training-based conventional least-squares estimation (CLSE) scheme and a closed-form semiblind (CFSB) scheme that employs training followed by infor-mation-bearing spectrally white data symbols. Employing matrix perturbation theory, we develop expressions for the mean-square error (MSE) in the beamforming vector, the average received signal-to-noise ratio (SNR) and the symbol error rate (SER) performance of both the semiblind and the conventional schemes. Finally, we describe a weighted linear combiner of the CFSB and CLSE estimates for additional improvement in performance. The analytical results are verified through Monte Carlo simulations. Index Terms—Beamforming, channel estimation, constrained estimation, Cramer–Rao bound, least squares, maximum ratio transmission (MRT), multiple-input multiple-output (MIMO), semiblind. I.
File Format	PDF
Journal	IEEE Trans, on Signal Processing
Language	English
Publisher Date	2006-01-01
Access Restriction	Open
Subject Keyword	Maximum Ratio Transmission Semiblind Channel Estimation Mimo System Training-based Conventional Least-squares Estimation Conventional Scheme Weighted Linear Combiner Channel Matrix Clse Estimate White Data Symbol Signal-to-noise Ratio Beamforming Vector Cramer Rao Bound Monte Carlo Simulation Additional Improvement Index Term Beamforming Flat-fading Channel Estimation Scheme Comparative Study Mean-square Error Multiple-input Multiple-output Receive Beamforming Vector Closed-form Semiblind Semiblind Multiple-input Multiple-output Symbol Error Rate Matrix Perturbation Theory Max-imum Ratio Transmission Analytical Result Channel Estimation
Content Type	Text
Resource Type	Article

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