A reduced-state-space markov chain monte carlo method for iterative spatial multiplexing MIMO

Ming Zhao; Zhenning Shi; Mark C. Reed

doi:10.1109/GLOCOMW.2009.5360771

A reduced-state-space markov chain monte carlo method for iterative spatial multiplexing MIMO

Ming Zhao^*, Zhenning Shi, Mark C. Reed

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

Abstract

Markov Chain Monte Carlo (MCMC) method applied as Multiple-Input-Multiple- Output (MIMO) detector has shown near capacity performance. However, the conventional MCMC method suffers from an error floor in the high signal-to-noise (SNR) region. This paper proposes a novel robust reduced-state- space MCMC (RSS-MCMC) method, which utilizes the a priori information for the first time to qualify the reliable decoded bits from the entire signal space. The new robust MCMC method is developed to deal with the unreliable bits by using the reliably decoded bit information to cancel the interference that they generate. The performance comparison shows that the new technique has improved performance compared to the conventional approach, and further complexity reduction can be obtained with the assistance of the a priori information. Furthermore, the complexity and performance tradeoff of the new method can be optimized for practical realizations.

Original language	English
Title of host publication	2009 IEEE Globecom Workshops, Gc Workshops 2009
DOIs	https://doi.org/10.1109/GLOCOMW.2009.5360771
Publication status	Published - 2009
Event	2009 IEEE Globecom Workshops, Gc Workshops 2009 - Honolulu, HI, United States Duration: 30 Nov 2009 → 4 Dec 2009

Publication series

Name	2009 IEEE Globecom Workshops, Gc Workshops 2009

Conference

Conference	2009 IEEE Globecom Workshops, Gc Workshops 2009
Country/Territory	United States
City	Honolulu, HI
Period	30/11/09 → 4/12/09

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10.1109/GLOCOMW.2009.5360771

Cite this

@inproceedings{6950ec4e80024e36a377206b86f2d053,

title = "A reduced-state-space markov chain monte carlo method for iterative spatial multiplexing MIMO",

abstract = "Markov Chain Monte Carlo (MCMC) method applied as Multiple-Input-Multiple- Output (MIMO) detector has shown near capacity performance. However, the conventional MCMC method suffers from an error floor in the high signal-to-noise (SNR) region. This paper proposes a novel robust reduced-state- space MCMC (RSS-MCMC) method, which utilizes the a priori information for the first time to qualify the reliable decoded bits from the entire signal space. The new robust MCMC method is developed to deal with the unreliable bits by using the reliably decoded bit information to cancel the interference that they generate. The performance comparison shows that the new technique has improved performance compared to the conventional approach, and further complexity reduction can be obtained with the assistance of the a priori information. Furthermore, the complexity and performance tradeoff of the new method can be optimized for practical realizations.",

author = "Ming Zhao and Zhenning Shi and Reed, {Mark C.}",

year = "2009",

doi = "10.1109/GLOCOMW.2009.5360771",

language = "English",

isbn = "9781424456260",

series = "2009 IEEE Globecom Workshops, Gc Workshops 2009",

booktitle = "2009 IEEE Globecom Workshops, Gc Workshops 2009",

note = "2009 IEEE Globecom Workshops, Gc Workshops 2009 ; Conference date: 30-11-2009 Through 04-12-2009",

}

Zhao, M, Shi, Z & Reed, MC 2009, A reduced-state-space markov chain monte carlo method for iterative spatial multiplexing MIMO. in 2009 IEEE Globecom Workshops, Gc Workshops 2009., 5360771, 2009 IEEE Globecom Workshops, Gc Workshops 2009, 2009 IEEE Globecom Workshops, Gc Workshops 2009, Honolulu, HI, United States, 30/11/09. https://doi.org/10.1109/GLOCOMW.2009.5360771

TY - GEN

T1 - A reduced-state-space markov chain monte carlo method for iterative spatial multiplexing MIMO

AU - Zhao, Ming

AU - Shi, Zhenning

AU - Reed, Mark C.

PY - 2009

Y1 - 2009

N2 - Markov Chain Monte Carlo (MCMC) method applied as Multiple-Input-Multiple- Output (MIMO) detector has shown near capacity performance. However, the conventional MCMC method suffers from an error floor in the high signal-to-noise (SNR) region. This paper proposes a novel robust reduced-state- space MCMC (RSS-MCMC) method, which utilizes the a priori information for the first time to qualify the reliable decoded bits from the entire signal space. The new robust MCMC method is developed to deal with the unreliable bits by using the reliably decoded bit information to cancel the interference that they generate. The performance comparison shows that the new technique has improved performance compared to the conventional approach, and further complexity reduction can be obtained with the assistance of the a priori information. Furthermore, the complexity and performance tradeoff of the new method can be optimized for practical realizations.

AB - Markov Chain Monte Carlo (MCMC) method applied as Multiple-Input-Multiple- Output (MIMO) detector has shown near capacity performance. However, the conventional MCMC method suffers from an error floor in the high signal-to-noise (SNR) region. This paper proposes a novel robust reduced-state- space MCMC (RSS-MCMC) method, which utilizes the a priori information for the first time to qualify the reliable decoded bits from the entire signal space. The new robust MCMC method is developed to deal with the unreliable bits by using the reliably decoded bit information to cancel the interference that they generate. The performance comparison shows that the new technique has improved performance compared to the conventional approach, and further complexity reduction can be obtained with the assistance of the a priori information. Furthermore, the complexity and performance tradeoff of the new method can be optimized for practical realizations.

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U2 - 10.1109/GLOCOMW.2009.5360771

DO - 10.1109/GLOCOMW.2009.5360771

M3 - Conference contribution

SN - 9781424456260

T3 - 2009 IEEE Globecom Workshops, Gc Workshops 2009

BT - 2009 IEEE Globecom Workshops, Gc Workshops 2009

T2 - 2009 IEEE Globecom Workshops, Gc Workshops 2009

Y2 - 30 November 2009 through 4 December 2009

ER -

A reduced-state-space markov chain monte carlo method for iterative spatial multiplexing MIMO

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