Data-Aided Autoregressive Sparse Channel Tracking for OFDM Systems

Büyükşar A. B., ŞENOL H., ERKÜÇÜK S., Çırpan H. A.

13th International Symposium on Wireless Communication Systems (ISWCS), Poznan, Poland, 20 - 23 September 2016, pp.424-428 identifier

  • Publication Type: Conference Paper / Full Text
  • City: Poznan
  • Country: Poland
  • Page Numbers: pp.424-428
  • Istanbul Technical University Affiliated: Yes


In order to meet future communication system requirements, channel estimation over fast fading and frequency selective channels is crucial. In this paper, Space Alternated Generalized Expectation Maximization Maximum a Posteriori (SAGE-MAP) based channel estimation algorithm is proposed for Orthogonal Frequency Division Multiplexing (OFDM) systems for Autoregressive (AR) modeled time-varying sparse channels. Also, an initialization algorithm has been developed from the widely used sparse approximation algorithm Orthogonal Matching Pursuit (OMP), since the performance of SAGE algorithm strictly depends on initialization. The results show that multipath delay positions can be tracked successfully for every time instant using the proposed SAGE-MAP based approach.