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

Title	Iterative near maximum-likelihood sequence detection for MIMO optical wireless systems
Author	Chatzidiamantis, N. D., Uysal, Murat, Tsiftsis, T. A., Karagiannidis, G. K.
Publication Date:	2010-04
Publication Place	- IEEE
Subject	Atmospheric turbulence, Expectation–maximization (EM) algorithm, Free-space optical communication, MLSD, Maximum-likelihood (ML) symbol-by-symbol detection, Spatial diversity
Type	Periodical
Language	English
Digital	Yes
Manuscript	No
Library:	Özyeğin University
Library Asset ID	0733-8724
Record ID	5409cd8c-c17e-4097-afe6-a50a4f651558
Library Location	Electrical & Electronics Engineering
Date	2010-04
Notes	Due to copyright restrictions, the access to the full text of this article is only available via subscription.
Sample Text	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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Özyeğin University

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

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

Publication Date 2010-04

Publication Place - IEEE

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

Type Periodical

Language English

Digital Yes

Manuscript No

Library Özyeğin University

Library Asset ID 0733-8724

Record ID 5409cd8c-c17e-4097-afe6-a50a4f651558

Library Location Electrical & Electronics Engineering

Date 2010-04

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

Sample Text 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