Analysis of low-complexity windowed DFT-based MMSE channel estimator for OFDM systems

Baoguo Yang, Zhigang Cao, Khaled Letaief

Research output: Contribution to journalArticle

157 Citations (Scopus)


Low-complexity windowed discrete Fourier transform (DFT)-based minimum mean square error (MMSE) channel estimators are proposed and analyzed for both the interpolation and noninterpolation cases for orthogonal frequency-division multiplexing (OFDM) mobile communications systems in this paper. In the proposed method, the frequency domain data windowing is used to reduce the aliasing errors for the interpolation case and get better noise filtering performance for the noninterpolation case. The time domain MMSE weighting is also used to suppress the channel noise for both cases. Moreover, the optimal generalized Hanning window shape is searched to minimize the channel estimation mean square error (MSE). Analysis and simulation results show that the proposed method performance is close to the optimal MMSE estimator and is much better than the direct DFT-based estimator for both cases. Compared with the optimal MMSE estimator, however, the computation load of the proposed method can be significantly reduced because the IDFT/DFT transforms can be implemented with the fast algorithms IFFT/FFT.

Original languageEnglish
Pages (from-to)1977-1987
Number of pages11
JournalIEEE Transactions on Communications
Issue number11
Publication statusPublished - Nov 2001
Externally publishedYes



  • Channel estimation
  • Fading radio channels
  • OFDM
  • Wireless communication systems

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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