Optimization of training sequences for spatially correlated MIMO-OFDM

  • Authors:

  • H. D. Tuan;V.-J. Luong;H. H. Nguyen

  • Affiliations:

  • School of Electrical Engineering and Telecommunication, University of New South Wales, UNSW Sydney, 2052, AUSTRALIA;School of Electrical Engineering and Telecommunication, University of New South Wales, UNSW Sydney, 2052, AUSTRALIA;Department of Electrical and Computer Engineering, University of Saskatchewan, Saskatoon, Canada

  • Venue:
  • ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
  • Year:
  • 2009

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Abstract

The optimal training sequence for channel estimation in spatially correlated multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems has not been found for an arbitrary signal-to-noise ratio (SNR). Only one class of training sequences was proposed in the literature in which the power allocation is given only for the extreme conditions of low and high SNR. Provided in this paper are (i) a necessary and sufficient condition for the optimal training sequence together with a convex programming to find the solution, and (ii) efficient procedures to find the optimal training sequence. Simulation results confirms the superiority of the proposed design over the existing one.