Tensor-based multi-carrier signal detection in the presence of phase noise

Weiming Yi; Wang Zuo; Wang Jing

doi:10.1109/IMCEC.2016.7867374

Tensor-based multi-carrier signal detection in the presence of phase noise

Weiming Yi, Wang Zuo, Wang Jing

School of Information and Electronics

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

1 Citation (Scopus)

Abstract

PHN (Phase Noise) can lead to CPE (Common Phase Error) and ICI (Inter-carrier Interference) especially in the Multi-Carrier transmission system. Most existing methods usually estimate the PHN by adding redundant pilots and virtual carriers and then recover the signals by the estimated PHN, which decrease the transmission efficiency. A tensor-based signal detection method is proposed to deal with the signals' recovery in wireless communication system with MIMO (Multiple-Input Multiple-Output) and OFDM (Orthogonal Frequency Division Multiplexing). The benefit of the proposed tensor-based method is that it can directly recover the received signals at the base station without estimating the phase noise in advance and can fulfill both the PHN estimation and the signal detection at the same time during the iterations. The proposed method also reduces the number of redundant pilots and virtual carriers, thus improves the data's transmission efficiency. Simulation results indicate that the proposed signal detection method can generate satisfied performance on BER (Bit Error Rate) and demonstrates the effectiveness of the tensor-based communication signal analysis method.

Original language	English
Title of host publication	Proceedings of 2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2016
Editors	Bing Xu
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1062-1066
Number of pages	5
ISBN (Electronic)	9781467396127
DOIs	https://doi.org/10.1109/IMCEC.2016.7867374
Publication status	Published - 28 Feb 2017
Event	2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2016 - Xi'an, China Duration: 3 Oct 2016 → 5 Oct 2016

Publication series

Name	Proceedings of 2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2016

Conference

Conference	2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2016
Country/Territory	China
City	Xi'an
Period	3/10/16 → 5/10/16

Keywords

MIMO (Multiple-Input Multiple-Output)
OFDM (Orthogonal Frequency Division Multiplexing)
PARAFAC (Parallel Factor) decomposition
PHN (Phase noise)
Tensor

Access to Document

10.1109/IMCEC.2016.7867374

Cite this

Yi, W., Zuo, W., & Jing, W. (2017). Tensor-based multi-carrier signal detection in the presence of phase noise. In B. Xu (Ed.), Proceedings of 2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2016 (pp. 1062-1066). Article 7867374 (Proceedings of 2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IMCEC.2016.7867374

Yi, Weiming ; Zuo, Wang ; Jing, Wang. / Tensor-based multi-carrier signal detection in the presence of phase noise. Proceedings of 2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2016. editor / Bing Xu. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 1062-1066 (Proceedings of 2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2016).

@inproceedings{3b84ccbc53244c249836d1b869aadfc8,

title = "Tensor-based multi-carrier signal detection in the presence of phase noise",

abstract = "PHN (Phase Noise) can lead to CPE (Common Phase Error) and ICI (Inter-carrier Interference) especially in the Multi-Carrier transmission system. Most existing methods usually estimate the PHN by adding redundant pilots and virtual carriers and then recover the signals by the estimated PHN, which decrease the transmission efficiency. A tensor-based signal detection method is proposed to deal with the signals' recovery in wireless communication system with MIMO (Multiple-Input Multiple-Output) and OFDM (Orthogonal Frequency Division Multiplexing). The benefit of the proposed tensor-based method is that it can directly recover the received signals at the base station without estimating the phase noise in advance and can fulfill both the PHN estimation and the signal detection at the same time during the iterations. The proposed method also reduces the number of redundant pilots and virtual carriers, thus improves the data's transmission efficiency. Simulation results indicate that the proposed signal detection method can generate satisfied performance on BER (Bit Error Rate) and demonstrates the effectiveness of the tensor-based communication signal analysis method.",

keywords = "MIMO (Multiple-Input Multiple-Output), OFDM (Orthogonal Frequency Division Multiplexing), PARAFAC (Parallel Factor) decomposition, PHN (Phase noise), Tensor",

author = "Weiming Yi and Wang Zuo and Wang Jing",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2016 ; Conference date: 03-10-2016 Through 05-10-2016",

year = "2017",

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language = "English",

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Yi, W, Zuo, W & Jing, W 2017, Tensor-based multi-carrier signal detection in the presence of phase noise. in B Xu (ed.), Proceedings of 2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2016., 7867374, Proceedings of 2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2016, Institute of Electrical and Electronics Engineers Inc., pp. 1062-1066, 2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2016, Xi'an, China, 3/10/16. https://doi.org/10.1109/IMCEC.2016.7867374

Tensor-based multi-carrier signal detection in the presence of phase noise. / Yi, Weiming; Zuo, Wang; Jing, Wang.
Proceedings of 2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2016. ed. / Bing Xu. Institute of Electrical and Electronics Engineers Inc., 2017. p. 1062-1066 7867374 (Proceedings of 2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2016).

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

TY - GEN

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AU - Yi, Weiming

AU - Zuo, Wang

AU - Jing, Wang

PY - 2017/2/28

Y1 - 2017/2/28

N2 - PHN (Phase Noise) can lead to CPE (Common Phase Error) and ICI (Inter-carrier Interference) especially in the Multi-Carrier transmission system. Most existing methods usually estimate the PHN by adding redundant pilots and virtual carriers and then recover the signals by the estimated PHN, which decrease the transmission efficiency. A tensor-based signal detection method is proposed to deal with the signals' recovery in wireless communication system with MIMO (Multiple-Input Multiple-Output) and OFDM (Orthogonal Frequency Division Multiplexing). The benefit of the proposed tensor-based method is that it can directly recover the received signals at the base station without estimating the phase noise in advance and can fulfill both the PHN estimation and the signal detection at the same time during the iterations. The proposed method also reduces the number of redundant pilots and virtual carriers, thus improves the data's transmission efficiency. Simulation results indicate that the proposed signal detection method can generate satisfied performance on BER (Bit Error Rate) and demonstrates the effectiveness of the tensor-based communication signal analysis method.

AB - PHN (Phase Noise) can lead to CPE (Common Phase Error) and ICI (Inter-carrier Interference) especially in the Multi-Carrier transmission system. Most existing methods usually estimate the PHN by adding redundant pilots and virtual carriers and then recover the signals by the estimated PHN, which decrease the transmission efficiency. A tensor-based signal detection method is proposed to deal with the signals' recovery in wireless communication system with MIMO (Multiple-Input Multiple-Output) and OFDM (Orthogonal Frequency Division Multiplexing). The benefit of the proposed tensor-based method is that it can directly recover the received signals at the base station without estimating the phase noise in advance and can fulfill both the PHN estimation and the signal detection at the same time during the iterations. The proposed method also reduces the number of redundant pilots and virtual carriers, thus improves the data's transmission efficiency. Simulation results indicate that the proposed signal detection method can generate satisfied performance on BER (Bit Error Rate) and demonstrates the effectiveness of the tensor-based communication signal analysis method.

KW - MIMO (Multiple-Input Multiple-Output)

KW - OFDM (Orthogonal Frequency Division Multiplexing)

KW - PARAFAC (Parallel Factor) decomposition

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BT - Proceedings of 2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2016

A2 - Xu, Bing

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2016

Y2 - 3 October 2016 through 5 October 2016

ER -

Yi W, Zuo W, Jing W. Tensor-based multi-carrier signal detection in the presence of phase noise. In Xu B, editor, Proceedings of 2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2016. Institute of Electrical and Electronics Engineers Inc. 2017. p. 1062-1066. 7867374. (Proceedings of 2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2016). doi: 10.1109/IMCEC.2016.7867374

Tensor-based multi-carrier signal detection in the presence of phase noise

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