Iterative channel estimation using virtual pilot signals for MIMO-OFDM systems

Sunho Park, Byonghyo Shim, Jun Won Choi

Research output: Contribution to journalArticlepeer-review

53 Citations (Scopus)


The number of transmit and receive antennas in multi-input multi-output (MIMO) systems is increasing rapidly to enhance the throughput and reliability of next-generation wireless systems. Benefits of large size MIMO systems, however, can be realized only when the quality of estimated channels is ensured at the transmitter and receiver side alike. In this paper, we introduce a new decision-directed channel estimation technique dealing with pilot shortage in the MIMO-OFDM systems. The proposed channel estimator uses soft symbol decisions obtained by iterative detection and decoding (IDD) scheme to enhance the quality of channel estimate. Using the soft information from the decoders, the proposed channel estimator selects reliable data tones, subtracts interstream interferences, and performs re-estimation of the channels. We analyze the optimal data tone selection criterion, which accounts for the reliability of symbol decisions and correlation of channels between the data tones and pilot tones. From numerical simulations, we show that the proposed channel estimator achieves considerable improvement in system performance over the conventional channel estimators in realistic MIMO-OFDM scenarios.

Original languageEnglish
Article number7067422
Pages (from-to)3032-3045
Number of pages14
JournalIEEE Transactions on Signal Processing
Issue number12
Publication statusPublished - 2015 Jun 15


  • Channel estimation
  • decision directed channel estimation
  • iterative detection and decoding
  • joint channel estimation and detection
  • multi-input multi-output (MIMO)
  • orthogonal frequency division multiplexing (OFDM)

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering


Dive into the research topics of 'Iterative channel estimation using virtual pilot signals for MIMO-OFDM systems'. Together they form a unique fingerprint.

Cite this