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Sparse Channel Estimation and Equalization for OFDM-Based Underwater Cooperative Systemsw with Amplify-and-Forward Relaying

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Date
2016
Author
Panayırcı, Erdal
Şenol, Habib
Uysal, Murat
Poor, H. Vincent
Abstract
This paper is concerned with a challenging problem of channel estimation and equalization for amplify-and-forward cooperative relay based orthogonal frequency division multi-plexing (OFDM) systems in sparse underwater acoustic (UWA) channels. The sparseness of the channel impulse response and prior information for the non-Gaussian channel gains modeled by an exact continuous Gaussian mixture (CGM) are exploited to improve the performance of the channel estimation algorithm. The resulting novel algorithm initially estimates the overall sparse complex-valued channel taps from the source to the destination as well as their locations using the matching pursuit (MP) approach. The effective time-domain non-Gaussian noise is approximated well as a Gaussian noise in the frequency-domain where the estimation takes place. An efficient and low complexity algorithm is developed based on a combination of the MP and the maximum a posteriori probability (MAP) based space-alternating generalized expectation-maximization technique to improve the estimates of the channel taps and their locations in an iterative manner. Computer simulations show that the UWA channel is estimated very effectively and the proposed algorithm exhibits excellent symbol error rate and channel estimation performance.

Source

IEEE Transactions on Signal Processing

Issue

1

Volume

64

Pages

214-228

URI

https://hdl.handle.net/20.500.12469/551
https://doi.org/10.1109/TSP.2015.2477807

Collections

  • Araştırma Çıktıları / Scopus [1565]
  • Araştırma Çıktıları / WOS [1518]
  • Elektrik-Elektronik Mühendisliği / Electrical - Electronics Engineering [320]

Keywords

AF relaying
Continuous Gaussian Mixture
Matching Pursuit
OFDM
Sage
Underwater Acoustic Channel Estimation

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DSpace software copyright © 2002-2015  DuraSpace
Contact Us | Send Feedback
Theme by 
@mire NV