Pilot Design for Gaussian Mixture Channel Estimation in Massive MIMO

Yujie Gu; Yimin D. Zhang

doi:10.1109/icassp.2018.8462013

Pilot Design for Gaussian Mixture Channel Estimation in Massive MIMO

Yujie Gu, Yimin D. Zhang

Temple University

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

7 Scopus citations

Abstract

Massive multiple-input multiple-output (MIMO) is a promising technique for 5G communications due to its superior spectrum and energy efficiencies. Despite its many advantages, the high number of antennas used in massive MIMO brings many challenges in practical implementations. Among them, the pilot overhead for downlink channel estimation becomes unaffordable in frequency division duplex (FDD) massive MIMO systems. In this paper, we exploit the available a priori knowledge of the channel to optimize the pilot design. By utilizing the low-rank nature of the channel matrix, we first derive the minimum number of pilot symbols required for perfect channel recovery. Further, under the general Gaussian mixture model for the channel vector, the pilot symbols are optimized to maximize the mutual information between the measurements of the user and the corresponding channel vector. Simulation results demonstrate the effectiveness of the proposed optimal pilot design for the downlink channel estimation in FDD massive MIMO systems.

Original language	English
Title of host publication	2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	3266-3270
Number of pages	5
ISBN (Print)	9781538646588
DOIs	https://doi.org/10.1109/icassp.2018.8462013
State	Published - 10 Sep 2018
Externally published	Yes
Event	2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Calgary, Canada Duration: 15 Apr 2018 → 20 Apr 2018

Publication series

Name	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume	2018-April
ISSN (Print)	1520-6149

Conference

Conference	2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018
Country/Territory	Canada
City	Calgary
Period	15/04/18 → 20/04/18

Bibliographical note

Publisher Copyright:
© 2018 IEEE.

Keywords

Channel estimation
Gaussian mixture
Massive MIMO
Pilot optimization

Access to Document

10.1109/icassp.2018.8462013

Cite this

Gu, Y., & Zhang, Y. D. (2018). Pilot Design for Gaussian Mixture Channel Estimation in Massive MIMO. In 2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Proceedings (pp. 3266-3270). Article 8462013 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; Vol. 2018-April). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/icassp.2018.8462013

Gu, Yujie ; Zhang, Yimin D. / Pilot Design for Gaussian Mixture Channel Estimation in Massive MIMO. 2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 3266-3270 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings).

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abstract = "Massive multiple-input multiple-output (MIMO) is a promising technique for 5G communications due to its superior spectrum and energy efficiencies. Despite its many advantages, the high number of antennas used in massive MIMO brings many challenges in practical implementations. Among them, the pilot overhead for downlink channel estimation becomes unaffordable in frequency division duplex (FDD) massive MIMO systems. In this paper, we exploit the available a priori knowledge of the channel to optimize the pilot design. By utilizing the low-rank nature of the channel matrix, we first derive the minimum number of pilot symbols required for perfect channel recovery. Further, under the general Gaussian mixture model for the channel vector, the pilot symbols are optimized to maximize the mutual information between the measurements of the user and the corresponding channel vector. Simulation results demonstrate the effectiveness of the proposed optimal pilot design for the downlink channel estimation in FDD massive MIMO systems.",

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Gu, Y & Zhang, YD 2018, Pilot Design for Gaussian Mixture Channel Estimation in Massive MIMO. in 2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Proceedings., 8462013, ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, vol. 2018-April, Institute of Electrical and Electronics Engineers Inc., pp. 3266-3270, 2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018, Calgary, Canada, 15/04/18. https://doi.org/10.1109/icassp.2018.8462013

Pilot Design for Gaussian Mixture Channel Estimation in Massive MIMO. / Gu, Yujie; Zhang, Yimin D.
2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2018. p. 3266-3270 8462013 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; Vol. 2018-April).

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

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AB - Massive multiple-input multiple-output (MIMO) is a promising technique for 5G communications due to its superior spectrum and energy efficiencies. Despite its many advantages, the high number of antennas used in massive MIMO brings many challenges in practical implementations. Among them, the pilot overhead for downlink channel estimation becomes unaffordable in frequency division duplex (FDD) massive MIMO systems. In this paper, we exploit the available a priori knowledge of the channel to optimize the pilot design. By utilizing the low-rank nature of the channel matrix, we first derive the minimum number of pilot symbols required for perfect channel recovery. Further, under the general Gaussian mixture model for the channel vector, the pilot symbols are optimized to maximize the mutual information between the measurements of the user and the corresponding channel vector. Simulation results demonstrate the effectiveness of the proposed optimal pilot design for the downlink channel estimation in FDD massive MIMO systems.

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Gu Y, Zhang YD. Pilot Design for Gaussian Mixture Channel Estimation in Massive MIMO. In 2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2018. p. 3266-3270. 8462013. (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings). doi: 10.1109/icassp.2018.8462013

Pilot Design for Gaussian Mixture Channel Estimation in Massive MIMO

Abstract

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Keywords

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