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Sparse channel estimation for OFDM-based underwater cooperative systems with amplify-and-forward relaying

Title	Sparse channel estimation for OFDM-based underwater cooperative systems with amplify-and-forward relaying
Author	Şenol, H., Panayırcı, E., Uysal, Murat
Publication Date:	2014
Publication Place	- IEEE
Subject	Gaussian noise, Gaussian processes, OFDM modulation, Amplify and forward communication, Channel estimation, Cooperative communication, Expectation-maximisation algorithm
Type	Document
Language	English
Digital	Yes
Manuscript	No
Library:	Özyeğin University
Library Asset ID	978-1-4799-4067-7
Record ID	5b501e2b-93a1-430c-909f-72357913a980
Library Location	Electrical & Electronics Engineering
Date	2014
Notes	Due to copyright restrictions, the access to the full text of this article is only available via subscription.
Sample Text	This paper is concerned with a challenging problem of channel estimation for amplify-and-forward cooperative relay based orthogonal frequency division multiplexing (OFDM) systems in the presence of sparse underwater acoustic channels and of the correlative non-Gaussian noise. We exploit the sparse structure of the channel impulse response to improve the performance of the channel estimation algorithm, due to the reduced number of taps to be estimated. The resulting novel algorithm initially estimates the overall sparse channel taps from the source to the destination as well as their locations using the matching pursuit (MP) approach. The correlated non-Gaussian effective noise is modeled as a Gaussian mixture. Based on the Gaussian mixture model, an efficient and low complexity algorithm is developed based on the combinations of the MP and the space-alternating generalized expectation-maximization (SAGE) technique, to improve the estimates of the channel taps and their location as well as the noise distribution parameters in an iterative way. The proposed SAGE algorithm is designed in such a way that, by choosing the admissible hidden data properly on which the SAGE algorithm relies, a subset of parameters is updated for analytical tractability and the remaining parameters for faster convergence Computer simulations show that underwater acoustic (UWA) channel is estimated very effectively and the proposed algorithm has excellent symbol error rate and channel estimation performance.
DOI	10.1109/BlackSeaCom.2014.6848994

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Özyeğin University

Sparse channel estimation for OFDM-based underwater cooperative systems with amplify-and-forward relaying

Author Şenol, H., Panayırcı, E., Uysal, Murat

Publication Date 2014

Publication Place - IEEE

Subject Gaussian noise, Gaussian processes, OFDM modulation, Amplify and forward communication, Channel estimation, Cooperative communication, Expectation-maximisation algorithm

Type Document

Language English

Digital Yes

Manuscript No

Library Özyeğin University

Library Asset ID 978-1-4799-4067-7

Record ID 5b501e2b-93a1-430c-909f-72357913a980

Library Location Electrical & Electronics Engineering

Date 2014

Notes Due to copyright restrictions, the access to the full text of this article is only available via subscription.

Sample Text This paper is concerned with a challenging problem of channel estimation for amplify-and-forward cooperative relay based orthogonal frequency division multiplexing (OFDM) systems in the presence of sparse underwater acoustic channels and of the correlative non-Gaussian noise. We exploit the sparse structure of the channel impulse response to improve the performance of the channel estimation algorithm, due to the reduced number of taps to be estimated. The resulting novel algorithm initially estimates the overall sparse channel taps from the source to the destination as well as their locations using the matching pursuit (MP) approach. The correlated non-Gaussian effective noise is modeled as a Gaussian mixture. Based on the Gaussian mixture model, an efficient and low complexity algorithm is developed based on the combinations of the MP and the space-alternating generalized expectation-maximization (SAGE) technique, to improve the estimates of the channel taps and their location as well as the noise distribution parameters in an iterative way. The proposed SAGE algorithm is designed in such a way that, by choosing the admissible hidden data properly on which the SAGE algorithm relies, a subset of parameters is updated for analytical tractability and the remaining parameters for faster convergence Computer simulations show that underwater acoustic (UWA) channel is estimated very effectively and the proposed algorithm has excellent symbol error rate and channel estimation performance.

DOI 10.1109/BlackSeaCom.2014.6848994