Iterative near maximum-likelihood sequence detection for MIMO optical wireless systems

Name: Iterative near maximum-likelihood sequence detection for MIMO optical wireless systems
Author: Chatzidiamantis, N. D., Uysal, Murat, Tsiftsis, T. A., Karagiannidis, G. K.

İsim	Iterative near maximum-likelihood sequence detection for MIMO optical wireless systems
Yazar	Chatzidiamantis, N. D., Uysal, Murat, Tsiftsis, T. A., Karagiannidis, G. K.
Basım Tarihi:	2010-04
Basım Yeri	- IEEE
Konu	Atmospheric turbulence, Expectation–maximization (EM) algorithm, Free-space optical communication, MLSD, Maximum-likelihood (ML) symbol-by-symbol detection, Spatial diversity
Tür	Süreli Yayın
Dil	İngilizce
Dijital	Evet
Yazma	Hayır
Kütüphane:	Özyeğin Üniversitesi
Demirbaş Numarası	0733-8724
Kayıt Numarası	5409cd8c-c17e-4097-afe6-a50a4f651558
Lokasyon	Electrical & Electronics Engineering
Tarih	2010-04
Notlar	Due to copyright restrictions, the access to the full text of this article is only available via subscription.
Örnek Metin	A major performance-limiting factor in terrestrial optical wireless (OW) systems is turbulence-induced fading. Exploiting the additional degrees of freedom in the spatial dimension, multiple laser transmitters combined with multiple receive apertures provide an effective solution for fading mitigation. Although multiple-input multiple-output (MIMO) OWsystems have been extensively studied in recent years, most of these works are mainly limited to symbol-by-symbol decoding. MLSD exploits the temporal correlation of turbulence-induced fading and promises further performance gains. In this paper, we investigate MLSD for intensity-modulation/direct-detection MIMO OW systems over log-normal atmospheric turbulence channels. Even with a low-order modulation scheme such as OOK, which is typically used inOWsystems, the complexity ofMLSD might be prohibitive. We therefore present an iterative sequence detector based on the expectation–maximization (EM) algorithm. The complexity of the proposed algorithm is considerably less than a direct evaluation of the log-likelihood function, and it is independent of the channel’s fading statistics. The Monte Carlo simulation results demonstrate that the EM-based algorithm outperforms the symbol-by-symbol decoder and achieves a performance, which lies within 0.3 dB of that of the optimal MLSD.
DOI	10.1109/JLT.2009.2038724
Cilt	28

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Iterative near maximum-likelihood sequence detection for MIMO optical wireless systems

Yazar Chatzidiamantis, N. D., Uysal, Murat, Tsiftsis, T. A., Karagiannidis, G. K.

Basım Tarihi 2010-04

Basım Yeri - IEEE

Konu Atmospheric turbulence, Expectation–maximization (EM) algorithm, Free-space optical communication, MLSD, Maximum-likelihood (ML) symbol-by-symbol detection, Spatial diversity

Tür Süreli Yayın

Dil İngilizce

Dijital Evet

Yazma Hayır

Kütüphane Özyeğin Üniversitesi

Demirbaş Numarası 0733-8724

Kayıt Numarası 5409cd8c-c17e-4097-afe6-a50a4f651558

Lokasyon Electrical & Electronics Engineering

Tarih 2010-04

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

Örnek Metin A major performance-limiting factor in terrestrial optical wireless (OW) systems is turbulence-induced fading. Exploiting the additional degrees of freedom in the spatial dimension, multiple laser transmitters combined with multiple receive apertures provide an effective solution for fading mitigation. Although multiple-input multiple-output (MIMO) OWsystems have been extensively studied in recent years, most of these works are mainly limited to symbol-by-symbol decoding. MLSD exploits the temporal correlation of turbulence-induced fading and promises further performance gains. In this paper, we investigate MLSD for intensity-modulation/direct-detection MIMO OW systems over log-normal atmospheric turbulence channels. Even with a low-order modulation scheme such as OOK, which is typically used inOWsystems, the complexity ofMLSD might be prohibitive. We therefore present an iterative sequence detector based on the expectation–maximization (EM) algorithm. The complexity of the proposed algorithm is considerably less than a direct evaluation of the log-likelihood function, and it is independent of the channel’s fading statistics. The Monte Carlo simulation results demonstrate that the EM-based algorithm outperforms the symbol-by-symbol decoder and achieves a performance, which lies within 0.3 dB of that of the optimal MLSD.

DOI 10.1109/JLT.2009.2038724

Cilt 28