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

  • Authors:

  • C.R. Murthy;A.K. Jagannatham;B.D. Rao

  • Affiliations:

  • Dept. of Electr. & Comput. Eng., Univ. of California, La Jolla, CA;-;-

  • Venue:
  • IEEE Transactions on Signal Processing
  • Year:
  • 2006

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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 maximum 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 information-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