Iterative SNR estimation using a priori information

  • Authors:

  • Nie Yuanfei;Ge Jianhua;Wang Yong

  • Affiliations:

  • State Key Laboratory of Integrated Service Networks, Xidian University, No. 2 Taibainan Street, Xi'an, China;State Key Laboratory of Integrated Service Networks, Xidian University, No. 2 Taibainan Street, Xi'an, China;State Key Laboratory of Integrated Service Networks, Xidian University, No. 2 Taibainan Street, Xi'an, China

  • Venue:
  • Digital Signal Processing
  • Year:
  • 2009

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Abstract

A class iterative signal-to-noise ratio (SNR) estimation algorithm is proposed in this paper. The data samples are governed by a given distribution with a priori. The expectation maximization (EM) algorithm is applied to iteratively maximize the likelihood function so as to realize the SNR estimation. Cramer-Rao bounds (CRB) with different a priori are compared for binary phase shift keying and orthogonal phase shift keying systems, which show the potential of the SNR estimator in turbo-like systems. In high-order modulations, simulation results show that the reduced-complexity iterative method with equal a priori has better performance in middle or high SNR region than the foregone ones. Moreover, the new method with feedback information is the best when its iteration number is 4 and extrinsic information larger than 0.4. These methods are applied in the bit-interleaved coded modulation with iterative decode (BICM-ID) system to validate the effect of the proposed methods.