Millimeter-wave Channel Estimation with Intelligent Reflecting  Surface Assisted Based on Vector Approximate Message Passing

WANG Dan; LIANG Jiamin; MEI Zhiqiang; LIU Jinzhi

doi:10.11999/JEIT211271

Volume 44 Issue 7

Jul. 2022

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Article Navigation > Journal of Electronics & Information Technology > 2022 > 44(7): 2400-2406

WANG Dan, LIANG Jiamin, MEI Zhiqiang, LIU Jinzhi. Millimeter-wave Channel Estimation with Intelligent Reflecting Surface Assisted Based on Vector Approximate Message Passing[J]. Journal of Electronics & Information Technology, 2022, 44(7): 2400-2406. doi: 10.11999/JEIT211271

Citation:

WANG Dan, LIANG Jiamin, MEI Zhiqiang, LIU Jinzhi. Millimeter-wave Channel Estimation with Intelligent Reflecting Surface Assisted Based on Vector Approximate Message Passing[J]. Journal of Electronics & Information Technology, 2022, 44(7): 2400-2406. doi: 10.11999/JEIT211271

Citation:

WANG Dan, LIANG Jiamin, MEI Zhiqiang, LIU Jinzhi. Millimeter-wave Channel Estimation with Intelligent Reflecting Surface Assisted Based on Vector Approximate Message Passing[J]. Journal of Electronics & Information Technology, 2022, 44(7): 2400-2406. doi: 10.11999/JEIT211271

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Millimeter-wave Channel Estimation with Intelligent Reflecting Surface Assisted Based on Vector Approximate Message Passing

doi: 10.11999/JEIT211271 cstr: 32379.14.JEIT211271

WANG Dan^{1, 2, 3},
LIANG Jiamin^{1
,
,},
MEI Zhiqiang¹,
LIU Jinzhi¹

1.
School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
2.
Chongqing Key Laboratory of Mobile Communications Technology, Chongqing 400065, China
3.
Engineering Research Center of Mobile Communications of the Ministry of Education, Chongqing 400065, China

Funds: The National Science and Technology Major Project (2017ZX03001021), Chongqing Natural Science Foundation Project (cstc2021jcyj-msxmX0454)

Received Date: 2021-11-16
Rev Recd Date: 2022-03-25

Available Online: 2022-04-02

Publish Date: 2022-07-25

Abstract

Abstract

Millimeter-wave is a typical line-of-sight transmission method, which is seriously affected by atmospheric absorption. Aiming at the limited non-line-of-sight propagation of millimeter waves, Intelligent Reflecting Surface (IRS) is used to assist millimeter-wave communications, and the Khatri-Rao product combined with the Vector Approximate Message Passing (KR-VAMP) algorithm is proposed, which can improve the channel estimation quality of the millimeter-wave communication systems. By adopting the Khatri-Rao product, the cascaded channel problem is transformed into a sparse signal recovery problem. The proposed algorithm combines with the advantages of the VAMP’s vector and iterative threshold algorithm. The number of training iterations and the channel estimation error are reduced in the IRS-assisted millimeter-wave system. Finally, based on simulation results, the influence of each variable on the Mean Square Error (MMSE) of channel estimation and the convergence of MMSE with the number of iterations are analyzed. It also verifies that the algorithm has better performance than other Approximate Message Passing (AMP) algorithms.
- Channel estimation,
- Intelligent Reflecting Surface(IRS),
- Millimeter-wave,
- Vector Approximate Message Passing(VAMP)

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References(19)

References

[1]	SAAD W, BENNIS M, and CHEN Mingzhe. A vision of 6G wireless systems: Applications, trends, technologies, and open research problems[J]. IEEE Network, 2020, 34(3): 134–142. doi: 10.1109/MNET.001.1900287
[2]	BASAR E, DI RENZO M, DE ROSNY J, et al. Wireless communications through reconfigurable intelligent surfaces[J]. IEEE Access, 2019, 7: 116753–116773. doi: 10.1109/ACCESS.2019.2935192
[3]	YOU Changsheng, ZHENG Beixiong, and ZHANG Rui. Intelligent reflecting surface with discrete phase shifts: Channel estimation and passive beamforming[C]. The ICC 2020–2020 IEEE International Conference on Communications (ICC), Dublin, Ireland, 2020: 1–6.
[4]	CHEN Jie, LIANG Yingchang, CHENG H V, et al. Channel estimation for reconfigurable intelligent surface aided multi-user MIMO systems[EB/OL]. https://arxiv.org/abs/1912.03619, 2019.
[5]	HE Zhenqing and YUAN Xiaojun. Cascaded channel estimation for large intelligent metasurface assisted massive MIMO[J]. IEEE Wireless Communications Letters, 2020, 9(2): 210–214. doi: 10.1109/LWC.2019.2948632
[6]	MIRZA J and ALI B. Channel estimation method and phase shift design for reconfigurable intelligent surface assisted MIMO networks[J]. IEEE Transactions on Cognitive Communications and Networking, 2021, 7(2): 441–451. doi: 10.1109/TCCN.2021.3072895
[7]	WANG Peilan, FANG Jun, and LI Hongbin. Joint beamforming for intelligent reflecting surface-assisted millimeter wave communications[EB/OL]. https://arxiv.org/abs/1910.08541v1, 2019.
[8]	TSAI C R, LIU Y H, and WU A Y. Efficient compressive channel estimation for millimeter-wave large-scale antenna systems[J]. IEEE Transactions on Signal Processing, 2018, 66(9): 2414–2428. doi: 10.1109/TSP.2018.2811742
[9]	TAHA A, ALRABEIAH M, and ALKHATEEB A. Enabling large intelligent surfaces with compressive sensing and deep learning[J]. IEEE Access, 2021, 9: 44304–44321. doi: 10.1109/ACCESS.2021.3064073
[10]	LIU Hang, YUAN Xiaojun, and ZHANG Y J A. Message-passing based channel estimation for reconfigurable intelligent surface assisted MIMO[C]. 2020 IEEE International Symposium on Information Theory (ISIT), Los Angeles, USA, 2020: 2983–2988.
[11]	NADEEM Q U A, ALWAZANI H, KAMMOUN A, et al. Intelligent reflecting surface-assisted multi-user MISO communication: Channel estimation and beamforming design[J]. IEEE Open Journal of the Communications Society, 2020, 1: 661–680. doi: 10.1109/OJCOMS.2020.2992791
[12]	ZHANG Jinming, QI Chenhao, LI Ping, et al. Channel estimation for reconfigurable intelligent surface aided massive MIMO system[C]. The 21st International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), Atlanta, USA, 2020.
[13]	TAN Xin, SUN Zhi, KOUTSONIKOLAS D, et al. Enabling indoor mobile millimeter-wave networks based on smart reflect-arrays[C]. The IEEE INFOCOM 2018 - IEEE Conference on Computer Communications, Honolulu, USA, 2018: 270–278.
[14]	DE ARAÚJO G T and DE ALMEIDA A L F. PARAFAC-based channel estimation for intelligent reflective surface assisted MIMO system[C]. The 11th Sensor Array and Multichannel Signal Processing Workshop (SAM), Hangzhou, China, 2020: 1–5.
[15]	WANG Peilan, FANG Jun, DUAN Huiping, et al. Compressed channel estimation for intelligent reflecting surface-assisted millimeter wave systems[J]. IEEE Signal Processing Letters, 2020, 27: 905–909. doi: 10.1109/LSP.2020.2998357
[16]	BARON D, RUSH C, and YAPICI Y. mmWave channel estimation via approximate message passing with side information[C]. The 21st International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), Atlanta, USA, 2020.
[17]	ABEYWICKRAMA S, ZHANG Rui, WU Qingqing, et al. Intelligent reflecting surface: Practical phase shift model and beamforming optimization[J]. IEEE Transactions on Communications, 2020, 68(9): 5849–5863. doi: 10.1109/TCOMM.2020.3001125
[18]	王丹, 梁家敏, 刘金枝, 等. 6G可重构智能表面的相移模型设计[J]. 计算机应用, 2021, 41(9): 2694–2698. doi: 10.11772/j.issn.1001-9081.2020111836 WANG Dan, LIANG Jiamin, LIU Jinzhi, et al. Phase shift model design for 6G reconfigurable intelligent surface[J]. Journal of Computer Applications, 2021, 41(9): 2694–2698. doi: 10.11772/j.issn.1001-9081.2020111836
[19]	RANGAN S, SCHNITER P, and FLETCHER A K. Vector approximate message passing[C]. 2017 IEEE International Symposium on Information Theory (ISIT), Aachen, Germany, 2017: 1588–1592.