A graphical model based frequency domain equalization for FTN signaling in doubly selective channels

Weijie YUAN; Nan WU; Xiaotong QI; Hua WANG; Jingming KUANG

doi:10.1109/PIMRC.2016.7794782

A graphical model based frequency domain equalization for FTN signaling in doubly selective channels

Weijie YUAN, Nan WU^*, Xiaotong QI, Hua WANG, Jingming KUANG

^*Corresponding author for this work

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Research › peer-review

Abstract

Modern mobile communication applications raise the requirement of high quality support for high mobility users. In this paper, we present a Bayesian graphical model based frequency domain equalization method for faster-than-Nyquist (FTN) signaling in doubly selective channels. The conventional frequency domain minimum mean squared error (FD-MMSE) equalizer suffers high complexity due to the interferences induced by adjacent frequency symbols. To tackle this problem, a low complexity iterative message passing method namely, belief propagation is employed on the Bayesian graphical model to detect the FTN symbols. Compared to the low complexity variational inference method, the proposed algorithm considers the conditional dependencies between symbols and therefore can improve the performance. Simulation results show that the proposed equalization method has similar performance of the MMSE equalizer and outperforms the variational inference method.

Original language	English
Title of host publication	2016 IEEE 27th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications, PIMRC 2016
Publisher	IEEE
ISBN (Electronic)	9781509032549
ISBN (Print)	9781509032556
DOIs	https://doi.org/10.1109/PIMRC.2016.7794782
Publication status	Published - 21 Dec 2016
Externally published	Yes
Event	27th IEEE Annual International Symposium on Personal, Indoor, and Mobile Radio Communications, PIMRC 2016 - Valencia, Spain Duration: 4 Sept 2016 → 8 Sept 2016

Conference

Conference	27th IEEE Annual International Symposium on Personal, Indoor, and Mobile Radio Communications, PIMRC 2016
Country/Territory	Spain
City	Valencia
Period	4/09/16 → 8/09/16

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

Keywords

Bayesian graphical model
belief propagation
Faster-than-Nyquist signaling
frequency domain equalization

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10.1109/PIMRC.2016.7794782

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title = "A graphical model based frequency domain equalization for FTN signaling in doubly selective channels",

abstract = "Modern mobile communication applications raise the requirement of high quality support for high mobility users. In this paper, we present a Bayesian graphical model based frequency domain equalization method for faster-than-Nyquist (FTN) signaling in doubly selective channels. The conventional frequency domain minimum mean squared error (FD-MMSE) equalizer suffers high complexity due to the interferences induced by adjacent frequency symbols. To tackle this problem, a low complexity iterative message passing method namely, belief propagation is employed on the Bayesian graphical model to detect the FTN symbols. Compared to the low complexity variational inference method, the proposed algorithm considers the conditional dependencies between symbols and therefore can improve the performance. Simulation results show that the proposed equalization method has similar performance of the MMSE equalizer and outperforms the variational inference method.",

keywords = "Bayesian graphical model, belief propagation, Faster-than-Nyquist signaling, frequency domain equalization",

author = "Weijie YUAN and Nan WU and Xiaotong QI and Hua WANG and Jingming KUANG",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 27th IEEE Annual International Symposium on Personal, Indoor, and Mobile Radio Communications, PIMRC 2016 ; Conference date: 04-09-2016 Through 08-09-2016",

year = "2016",

month = dec,

day = "21",

doi = "10.1109/PIMRC.2016.7794782",

language = "English",

isbn = "9781509032556",

booktitle = "2016 IEEE 27th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications, PIMRC 2016",

publisher = "IEEE",

}

YUAN, W, WU, N, QI, X, WANG, H & KUANG, J 2016, A graphical model based frequency domain equalization for FTN signaling in doubly selective channels. in 2016 IEEE 27th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications, PIMRC 2016., 7794782, IEEE, 27th IEEE Annual International Symposium on Personal, Indoor, and Mobile Radio Communications, PIMRC 2016, Valencia, Spain, 4/09/16. https://doi.org/10.1109/PIMRC.2016.7794782

A graphical model based frequency domain equalization for FTN signaling in doubly selective channels. / YUAN, Weijie; WU, Nan; QI, Xiaotong et al.
2016 IEEE 27th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications, PIMRC 2016. IEEE, 2016. 7794782.

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Research › peer-review

TY - GEN

T1 - A graphical model based frequency domain equalization for FTN signaling in doubly selective channels

AU - YUAN, Weijie

AU - WU, Nan

AU - QI, Xiaotong

AU - WANG, Hua

AU - KUANG, Jingming

PY - 2016/12/21

Y1 - 2016/12/21

N2 - Modern mobile communication applications raise the requirement of high quality support for high mobility users. In this paper, we present a Bayesian graphical model based frequency domain equalization method for faster-than-Nyquist (FTN) signaling in doubly selective channels. The conventional frequency domain minimum mean squared error (FD-MMSE) equalizer suffers high complexity due to the interferences induced by adjacent frequency symbols. To tackle this problem, a low complexity iterative message passing method namely, belief propagation is employed on the Bayesian graphical model to detect the FTN symbols. Compared to the low complexity variational inference method, the proposed algorithm considers the conditional dependencies between symbols and therefore can improve the performance. Simulation results show that the proposed equalization method has similar performance of the MMSE equalizer and outperforms the variational inference method.

AB - Modern mobile communication applications raise the requirement of high quality support for high mobility users. In this paper, we present a Bayesian graphical model based frequency domain equalization method for faster-than-Nyquist (FTN) signaling in doubly selective channels. The conventional frequency domain minimum mean squared error (FD-MMSE) equalizer suffers high complexity due to the interferences induced by adjacent frequency symbols. To tackle this problem, a low complexity iterative message passing method namely, belief propagation is employed on the Bayesian graphical model to detect the FTN symbols. Compared to the low complexity variational inference method, the proposed algorithm considers the conditional dependencies between symbols and therefore can improve the performance. Simulation results show that the proposed equalization method has similar performance of the MMSE equalizer and outperforms the variational inference method.

KW - Bayesian graphical model

KW - belief propagation

KW - Faster-than-Nyquist signaling

KW - frequency domain equalization

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M3 - Conference paper (refereed)

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SN - 9781509032556

BT - 2016 IEEE 27th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications, PIMRC 2016

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T2 - 27th IEEE Annual International Symposium on Personal, Indoor, and Mobile Radio Communications, PIMRC 2016

Y2 - 4 September 2016 through 8 September 2016

ER -

A graphical model based frequency domain equalization for FTN signaling in doubly selective channels

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