Blind OFDM channel estimation using FIR constraints: Reduced complexity and identifiability

Seongwook Song, Andrew C. Singer

Research output: Contribution to journalArticlepeer-review


In this correspondence, blind channel estimators exploiting finite alphabet constraints are discussed for orthogonal frequency-division multiplexing (OFDM) systems. Considering the channel and data jointly, a joint maximum-likelihood (JML) algorithm is described, along with identifiability conditions in the noise-free case. This approach enables development of general identifiability conditions for the minimum-distance (MD) finite alphabet blind algorithm of Zhou and Giannakis. Both the JML and MD algorithms suffer from high numerical complexity, as they rely on exhaustive search methods to resolve a large number of ambiguities. We present a substantially more efficient blind algorithm, the reduced complexity minimum distance (RMD) algorithm, by exploiting properties of the assumed finite-length impulse response (FIR) channel. The RMD algorithm exploits constraints on the unwrapped phase of FIR systems and results in significant reductions in numerical complexity over existing methods. In many cases, the RMD approach is able to completely eliminate the exhaustive search of the JML and MD approaches, while providing channel estimates of the same quality.

Original languageEnglish (US)
Pages (from-to)1136-1147
Number of pages12
JournalIEEE Transactions on Information Theory
Issue number3
StatePublished - Mar 2007


  • Blind channel estimation
  • Finite-length impulse response (FIR)
  • Orthogonal frequency-division multiplexing (OFDM)

ASJC Scopus subject areas

  • Information Systems
  • Computer Science Applications
  • Library and Information Sciences


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