Loading...

A MAP-Based order estimation procedure for Sparse channel estimation

Daei, S ; Sharif University of Technology | 2015

743 Viewed
  1. Type of Document: Article
  2. DOI: 10.1007/978-3-319-22482-4_40
  3. Publisher: Springer Verlag , 2015
  4. Abstract:
  5. Recently, there has been a growing interest in estimation of sparse channels as they are observed in underwater acoustic and ultrawideband channels. In this paper we present a new Bayesian sparse channel estimation (SCE) algorithm that, unlike traditional SCE methods, exploits noise statistical information to improve the estimates. The proposed method uses approximate maximum a posteriori probability (MAP) to detect the non-zero channel tap locations while least square estimation is used to determine the values of the channel taps. Computer simulations shows that the proposed algorithm outperforms the existing algorithms in terms of normalized mean squared error (NMSE) and approaches Cram´er-Rao lower bound of the estimation. In addition, it has low computational cost when compared to the other algorithms
  6. Keywords:
  7. Cramér-Rao lower bound ; Algorithms ; Least squares approximations ; Mean square error ; Probability distributions ; Underwater acoustics ; Bayesian ; Least square estimation ; Lower bounds ; Maximum A posteriori probabilities ; Normalized mean squared errors ; Sparse channel estimations ; Statistical information ; Ultra-wideband channels ; Channel estimation
  8. Source: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 25 2015 through 28 August 2015 ; Volume 9237 , August , 2015 , Pages 344-351 ; 03029743 (ISSN) ; 9783319224817 (ISBN)
  9. URL: http://link.springer.com/chapter/10.1007%2F978-3-319-22482-4_40