Probabilistic Behavior Analysis of MIMO Fading Channels under Geometric Mean Decomposition
Geometric mean decomposition (GMD) has been proposed as a method to realize multiple spatial links with identical gains that are intrinsic to a MIMO channel. In order to simplify system design and implementation based on knowledge regarding probability behavior of MIMO-GMD schemes, the main objectiv...
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| Format: | Article |
| Language: | English |
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Wiley
2012-01-01
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| Series: | Journal of Electrical and Computer Engineering |
| Online Access: | http://dx.doi.org/10.1155/2012/340809 |
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| _version_ | 1841524408026398720 |
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| author | Ping-Heng Kuo Pang-An Ting |
| author_facet | Ping-Heng Kuo Pang-An Ting |
| author_sort | Ping-Heng Kuo |
| collection | DOAJ |
| description | Geometric mean decomposition (GMD) has been proposed as a method to realize multiple spatial links with identical gains that are intrinsic to a MIMO channel. In order to simplify system design and implementation based on knowledge regarding probability behavior of MIMO-GMD schemes, the main objective of this paper is to statistically characterize the link gains and channel capacities that can be provided via GMD. In particular, closed-form univariate and bivariate probability density functions (PDFs) for these metrics under Rayleigh fading are derived using Gamma approximations. By applying these analytical results, the fluctuations of MIMO-GMD schemes are examined by modeling both link gains and capacities using finite-state Markov chains (FSMCs). |
| format | Article |
| id | doaj-art-a1bbc0ba35ae40e9830c36ae54c4513b |
| institution | Kabale University |
| issn | 2090-0147 2090-0155 |
| language | English |
| publishDate | 2012-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Electrical and Computer Engineering |
| spelling | doaj-art-a1bbc0ba35ae40e9830c36ae54c4513b2025-02-03T05:53:16ZengWileyJournal of Electrical and Computer Engineering2090-01472090-01552012-01-01201210.1155/2012/340809340809Probabilistic Behavior Analysis of MIMO Fading Channels under Geometric Mean DecompositionPing-Heng Kuo0Pang-An Ting1Information and Communications Research Laboratories, Industrial Technology Research Institute (ITRI), Chutung, Hsinchu 31040, TaiwanInformation and Communications Research Laboratories, Industrial Technology Research Institute (ITRI), Chutung, Hsinchu 31040, TaiwanGeometric mean decomposition (GMD) has been proposed as a method to realize multiple spatial links with identical gains that are intrinsic to a MIMO channel. In order to simplify system design and implementation based on knowledge regarding probability behavior of MIMO-GMD schemes, the main objective of this paper is to statistically characterize the link gains and channel capacities that can be provided via GMD. In particular, closed-form univariate and bivariate probability density functions (PDFs) for these metrics under Rayleigh fading are derived using Gamma approximations. By applying these analytical results, the fluctuations of MIMO-GMD schemes are examined by modeling both link gains and capacities using finite-state Markov chains (FSMCs).http://dx.doi.org/10.1155/2012/340809 |
| spellingShingle | Ping-Heng Kuo Pang-An Ting Probabilistic Behavior Analysis of MIMO Fading Channels under Geometric Mean Decomposition Journal of Electrical and Computer Engineering |
| title | Probabilistic Behavior Analysis of MIMO Fading Channels under Geometric Mean Decomposition |
| title_full | Probabilistic Behavior Analysis of MIMO Fading Channels under Geometric Mean Decomposition |
| title_fullStr | Probabilistic Behavior Analysis of MIMO Fading Channels under Geometric Mean Decomposition |
| title_full_unstemmed | Probabilistic Behavior Analysis of MIMO Fading Channels under Geometric Mean Decomposition |
| title_short | Probabilistic Behavior Analysis of MIMO Fading Channels under Geometric Mean Decomposition |
| title_sort | probabilistic behavior analysis of mimo fading channels under geometric mean decomposition |
| url | http://dx.doi.org/10.1155/2012/340809 |
| work_keys_str_mv | AT pinghengkuo probabilisticbehavioranalysisofmimofadingchannelsundergeometricmeandecomposition AT panganting probabilisticbehavioranalysisofmimofadingchannelsundergeometricmeandecomposition |