On training optimization for estimation of correlated MIMO channels in the presence of multiuser interference

Dimitrios Katselis, Eleftherios Kofidis, Sergios Theodoridis

Research output: Contribution to journalArticlepeer-review


In this paper, the problem of estimating multiple-input multiple-output (MIMO) channels in a realistic environment involving correlated channel fading and multiuser interference is considered. Four estimation schemes are studied, including the linear minimum mean squared error (LMMSE), least squares (LS), and Gauss-Markov (GM) estimators, as well as a novel scheme which is derived here as an alternative to LMMSE estimation. The MSE-optimal training sequences for each of them are provided and their requirements for side information feedback are assessed. The new scheme is shown to exhibit a performance comparable to or even better than LMMSE, at a significantly lower feedback and computational cost. The analytical comparison of the estimation schemes is supported by numerous simulation results that cover a wide range of antenna configurations, relative interference power, and channel correlation strengths. The results of this paper provide a complete picture for a palette of estimation schemes, with their relative performance and costs of training.

Original languageEnglish (US)
Pages (from-to)4892-4904
Number of pages13
JournalIEEE Transactions on Signal Processing
Issue number10 I
StatePublished - 2008
Externally publishedYes


  • Beamforming
  • Channel estimation
  • Covariance feedback
  • Flat fading
  • Gauss-Markov (GM)
  • Interference suppression
  • Least squares (LS)
  • Minimum mean squared error (MMSE)
  • Multiple-input multiple-output (MIMO)
  • Power allocation
  • Training
  • Water filling

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering


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