Low-Complexity MMSE Signal Detection Based on the AOR Iterative Algorithm for Uplink Massive MIMO Systems

Zhenyu Zhang; Yuanyuan Dong; Zhongshan Zhang; Xiyuan Wang; Xiaoming Dai; Linglong Dai; Haijun Zhang

doi:10.1007/978-3-319-72823-0_36

Low-Complexity MMSE Signal Detection Based on the AOR Iterative Algorithm for Uplink Massive MIMO Systems

Zhenyu Zhang, Yuanyuan Dong, Zhongshan Zhang, Xiyuan Wang, Xiaoming Dai^*, Linglong Dai, Haijun Zhang

^*Corresponding author for this work

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

Abstract

Massive multiple-input multiple-output (MIMO) systems can substantially improve the spectral efficiency and system capacity by equipping a large number of antennas at the base station and it is envisaged to be one of the critical technologies in the next generation of wireless communication systems. However, the computational complexity of the signal detection in massive MIMO systems presents a significant challenge for practical hardware implementations. This work proposed a novel minimum mean square error (MMSE) signal detection method based on the accelerated overrelaxation (AOR) iterative algorithm. The proposed AOR-based method can reduce the overall complexity of the classical MMSE signal detection by an order of magnitude from O(K³) to O(K²), where K is the number of users. Numerical results illustrate that the proposed AOR-based algorithm can outperform the performance of the recently proposed Neumann series approximation-based algorithm and approach the conventional MMSE signal detection involving exact matrix inversion with significantly reduced complexity.

Original language	English
Title of host publication	5G for Future Wireless Networks - 1st International Conference, 5GWN 2017, Proceedings
Editors	Zhiyong Feng, Yonghui Li, Victor C.M. Leung, Keping Long, Haijun Zhang, Zhongshan Zhang
Publisher	Springer Verlag
Pages	385-394
Number of pages	10
ISBN (Print)	9783319728223
DOIs	https://doi.org/10.1007/978-3-319-72823-0_36
Publication status	Published - 2018
Externally published	Yes
Event	1st International Conference on 5G for Future Wireless Networks, 5GWN 2017 - Beijing, China Duration: 21 Apr 2017 → 23 Apr 2017

Publication series

Name	Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
Volume	211
ISSN (Print)	1867-8211

Conference

Conference	1st International Conference on 5G for Future Wireless Networks, 5GWN 2017
Country/Territory	China
City	Beijing
Period	21/04/17 → 23/04/17

Keywords

Accelerated overrelaxation (AOR)
Complexity
Convergence
Iterative algorithm
Minimum mean square error (MMSE)

Access to Document

10.1007/978-3-319-72823-0_36

Cite this

Zhang, Z., Dong, Y., Zhang, Z., Wang, X., Dai, X., Dai, L., & Zhang, H. (2018). Low-Complexity MMSE Signal Detection Based on the AOR Iterative Algorithm for Uplink Massive MIMO Systems. In Z. Feng, Y. Li, V. C. M. Leung, K. Long, H. Zhang, & Z. Zhang (Eds.), 5G for Future Wireless Networks - 1st International Conference, 5GWN 2017, Proceedings (pp. 385-394). (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST; Vol. 211). Springer Verlag. https://doi.org/10.1007/978-3-319-72823-0_36

Zhang, Zhenyu ; Dong, Yuanyuan ; Zhang, Zhongshan et al. / Low-Complexity MMSE Signal Detection Based on the AOR Iterative Algorithm for Uplink Massive MIMO Systems. 5G for Future Wireless Networks - 1st International Conference, 5GWN 2017, Proceedings. editor / Zhiyong Feng ; Yonghui Li ; Victor C.M. Leung ; Keping Long ; Haijun Zhang ; Zhongshan Zhang. Springer Verlag, 2018. pp. 385-394 (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST).

@inproceedings{6164438ba662443582031912d31d1656,

title = "Low-Complexity MMSE Signal Detection Based on the AOR Iterative Algorithm for Uplink Massive MIMO Systems",

abstract = "Massive multiple-input multiple-output (MIMO) systems can substantially improve the spectral efficiency and system capacity by equipping a large number of antennas at the base station and it is envisaged to be one of the critical technologies in the next generation of wireless communication systems. However, the computational complexity of the signal detection in massive MIMO systems presents a significant challenge for practical hardware implementations. This work proposed a novel minimum mean square error (MMSE) signal detection method based on the accelerated overrelaxation (AOR) iterative algorithm. The proposed AOR-based method can reduce the overall complexity of the classical MMSE signal detection by an order of magnitude from O(K3) to O(K2), where K is the number of users. Numerical results illustrate that the proposed AOR-based algorithm can outperform the performance of the recently proposed Neumann series approximation-based algorithm and approach the conventional MMSE signal detection involving exact matrix inversion with significantly reduced complexity.",

keywords = "Accelerated overrelaxation (AOR), Complexity, Convergence, Iterative algorithm, Minimum mean square error (MMSE)",

author = "Zhenyu Zhang and Yuanyuan Dong and Zhongshan Zhang and Xiyuan Wang and Xiaoming Dai and Linglong Dai and Haijun Zhang",

note = "Publisher Copyright: {\textcopyright} 2018, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.; 1st International Conference on 5G for Future Wireless Networks, 5GWN 2017 ; Conference date: 21-04-2017 Through 23-04-2017",

year = "2018",

doi = "10.1007/978-3-319-72823-0_36",

language = "English",

isbn = "9783319728223",

series = "Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST",

publisher = "Springer Verlag",

pages = "385--394",

editor = "Zhiyong Feng and Yonghui Li and Leung, {Victor C.M.} and Keping Long and Haijun Zhang and Zhongshan Zhang",

booktitle = "5G for Future Wireless Networks - 1st International Conference, 5GWN 2017, Proceedings",

address = "Germany",

}

Zhang, Z, Dong, Y, Zhang, Z, Wang, X, Dai, X, Dai, L & Zhang, H 2018, Low-Complexity MMSE Signal Detection Based on the AOR Iterative Algorithm for Uplink Massive MIMO Systems. in Z Feng, Y Li, VCM Leung, K Long, H Zhang & Z Zhang (eds), 5G for Future Wireless Networks - 1st International Conference, 5GWN 2017, Proceedings. Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, vol. 211, Springer Verlag, pp. 385-394, 1st International Conference on 5G for Future Wireless Networks, 5GWN 2017, Beijing, China, 21/04/17. https://doi.org/10.1007/978-3-319-72823-0_36

Low-Complexity MMSE Signal Detection Based on the AOR Iterative Algorithm for Uplink Massive MIMO Systems. / Zhang, Zhenyu; Dong, Yuanyuan; Zhang, Zhongshan et al.
5G for Future Wireless Networks - 1st International Conference, 5GWN 2017, Proceedings. ed. / Zhiyong Feng; Yonghui Li; Victor C.M. Leung; Keping Long; Haijun Zhang; Zhongshan Zhang. Springer Verlag, 2018. p. 385-394 (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST; Vol. 211).

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

TY - GEN

T1 - Low-Complexity MMSE Signal Detection Based on the AOR Iterative Algorithm for Uplink Massive MIMO Systems

AU - Zhang, Zhenyu

AU - Dong, Yuanyuan

AU - Zhang, Zhongshan

AU - Wang, Xiyuan

AU - Dai, Xiaoming

AU - Dai, Linglong

AU - Zhang, Haijun

PY - 2018

Y1 - 2018

N2 - Massive multiple-input multiple-output (MIMO) systems can substantially improve the spectral efficiency and system capacity by equipping a large number of antennas at the base station and it is envisaged to be one of the critical technologies in the next generation of wireless communication systems. However, the computational complexity of the signal detection in massive MIMO systems presents a significant challenge for practical hardware implementations. This work proposed a novel minimum mean square error (MMSE) signal detection method based on the accelerated overrelaxation (AOR) iterative algorithm. The proposed AOR-based method can reduce the overall complexity of the classical MMSE signal detection by an order of magnitude from O(K3) to O(K2), where K is the number of users. Numerical results illustrate that the proposed AOR-based algorithm can outperform the performance of the recently proposed Neumann series approximation-based algorithm and approach the conventional MMSE signal detection involving exact matrix inversion with significantly reduced complexity.

AB - Massive multiple-input multiple-output (MIMO) systems can substantially improve the spectral efficiency and system capacity by equipping a large number of antennas at the base station and it is envisaged to be one of the critical technologies in the next generation of wireless communication systems. However, the computational complexity of the signal detection in massive MIMO systems presents a significant challenge for practical hardware implementations. This work proposed a novel minimum mean square error (MMSE) signal detection method based on the accelerated overrelaxation (AOR) iterative algorithm. The proposed AOR-based method can reduce the overall complexity of the classical MMSE signal detection by an order of magnitude from O(K3) to O(K2), where K is the number of users. Numerical results illustrate that the proposed AOR-based algorithm can outperform the performance of the recently proposed Neumann series approximation-based algorithm and approach the conventional MMSE signal detection involving exact matrix inversion with significantly reduced complexity.

KW - Accelerated overrelaxation (AOR)

KW - Complexity

KW - Convergence

KW - Iterative algorithm

KW - Minimum mean square error (MMSE)

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U2 - 10.1007/978-3-319-72823-0_36

DO - 10.1007/978-3-319-72823-0_36

M3 - Conference contribution

AN - SCOPUS:85040228559

SN - 9783319728223

T3 - Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST

SP - 385

EP - 394

BT - 5G for Future Wireless Networks - 1st International Conference, 5GWN 2017, Proceedings

A2 - Feng, Zhiyong

A2 - Li, Yonghui

A2 - Leung, Victor C.M.

A2 - Long, Keping

A2 - Zhang, Haijun

A2 - Zhang, Zhongshan

PB - Springer Verlag

T2 - 1st International Conference on 5G for Future Wireless Networks, 5GWN 2017

Y2 - 21 April 2017 through 23 April 2017

ER -

Zhang Z, Dong Y, Zhang Z, Wang X, Dai X, Dai L et al. Low-Complexity MMSE Signal Detection Based on the AOR Iterative Algorithm for Uplink Massive MIMO Systems. In Feng Z, Li Y, Leung VCM, Long K, Zhang H, Zhang Z, editors, 5G for Future Wireless Networks - 1st International Conference, 5GWN 2017, Proceedings. Springer Verlag. 2018. p. 385-394. (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST). doi: 10.1007/978-3-319-72823-0_36

Low-Complexity MMSE Signal Detection Based on the AOR Iterative Algorithm for Uplink Massive MIMO Systems

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