Subspace-Based Estimation of Rapidly Varying Mobile Channels for OFDM Systems

Research output: Contribution to journalArticlepeer-review

15 Scopus citations


It is well-known that time-varying channels can provide time diversity and improve error rate performance compared to time-invariant fading channels. However, exploiting time diversity requires very accurate channel estimates at the receiver. In order to reduce the number of unknown channel coefficients while estimating the time-varying channel, basis expansion models can be used along with long transmission frames that contain multiple orthogonal frequency division multiplexing (OFDM) symbols that experience the channel variation. The design of these OFDM frames need to judiciously incorporate training and data insertions in the transmitted signal while maintaining orthogonality. In this work, we propose an inter channel interference (ICI)-free training model depending on pilot symbols only and provide a corresponding time-varying channel estimation method. This scheme relies on an algorithm to determine the number of OFDM symbols per frame and the number of basis functions per path with minimal information about the Doppler bandwidth. As a performance benchmark, Bayesian Cramér Rao lower bound (CRLB) and the corresponding MSE bound are derived analytically for the proposed training model. Theoretical MSE expressions of the proposed estimation scheme are also derived as well as the MSE expressions in the presence of Doppler frequency mismatch. Simulations exhibit substantial MSE improvement and the corresponding Symbol Error Rate (SER) performances of the low complexity estimation scheme. They also corroborate that, unlike the common results in the literature, an OFDM system can perform better as the Doppler frequency increases with judicious design of training and channel estimation schemes.

Original languageEnglish (US)
Article number9296822
Pages (from-to)385-400
Number of pages16
JournalIEEE Transactions on Signal Processing
StatePublished - 2021


  • Basis expansion model (BEM)
  • channel estimation
  • null space
  • orthogonal frequency-division multiplexing (OFDM)
  • rapidly varying multipath channel

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering


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