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

Name: Sparse channel estimation and equalization for OFDM-based underwater cooperative systems with amplify-and-forward relaying
Author: Panayırcı, E., Şenol, H., Uysal, Murat, Poor, H. V.

İsim	Sparse channel estimation and equalization for OFDM-based underwater cooperative systems with amplify-and-forward relaying
Yazar	Panayırcı, E., Şenol, H., Uysal, Murat, Poor, H. V.
Basım Tarihi:	2016-01-01
Basım Yeri	- IEEE
Konu	Underwater Acoustic Channel Estimation, OFDM, AF Relaying, SAGE, Matching Pursuit, Continuous gaussian mixture
Tür	Süreli Yayın
Dil	İngilizce
Dijital	Evet
Yazma	Hayır
Kütüphane:	Özyeğin Üniversitesi
Demirbaş Numarası	1053-587X
Kayıt Numarası	c44832f5-8974-456e-9184-d3688cbf4b08
Lokasyon	Electrical & Electronics Engineering
Tarih	2016-01-01
Notlar	Due to copyright restrictions, the access to the full text of this article is only available via subscription.
Örnek Metin	This paper is concerned with a challenging problem of channel estimation and equalization for amplifyand- forward cooperative relay based orthogonal frequency division multiplexing (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 the combinations of the MP and the maximum a posteriori probability (MAP) based space-alternating generalized expectationmaximization technique, to improve the estimates of the channel taps and their locations in an iterative way. Computer simulations show that the UWA channel is estimated very effectively and the proposed algorithm exhibits excellent symbol error rate and channel estimation performance.

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

Yazar Panayırcı, E., Şenol, H., Uysal, Murat, Poor, H. V.

Basım Tarihi 2016-01-01

Basım Yeri - IEEE

Konu Underwater Acoustic Channel Estimation, OFDM, AF Relaying, SAGE, Matching Pursuit, Continuous gaussian mixture

Tür Süreli Yayın

Dil İngilizce

Dijital Evet

Yazma Hayır

Kütüphane Özyeğin Üniversitesi

Demirbaş Numarası 1053-587X

Kayıt Numarası c44832f5-8974-456e-9184-d3688cbf4b08

Lokasyon Electrical & Electronics Engineering

Tarih 2016-01-01

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

Örnek Metin This paper is concerned with a challenging problem of channel estimation and equalization for amplifyand- forward cooperative relay based orthogonal frequency division multiplexing (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 the combinations of the MP and the maximum a posteriori probability (MAP) based space-alternating generalized expectationmaximization technique, to improve the estimates of the channel taps and their locations in an iterative way. Computer simulations show that the UWA channel is estimated very effectively and the proposed algorithm exhibits excellent symbol error rate and channel estimation performance.