Location-driven beamforming for massive multi-user MIMO systems

doi:10.23919/JSEE.2023.000163

Journal of Systems Engineering and Electronics ›› 2025, Vol. 36 ›› Issue (3): 609-622.doi: 10.23919/JSEE.2023.000163

• ELECTRONICS TECHNOLOGY • Previous Articles

Location-driven beamforming for massive multi-user MIMO systems

Tao MA¹(), Jun HUANG¹(), Jiahao ZU²^,*(), Wen’gang LI²()

¹ Institute of Electronic Countermeasure, National University of Defense Technology, Hefei 230037, China
² School of Telecommunications Engineering Xidian University, Xi’an 710071, China

Received:2022-11-04 Online:2025-06-18 Published:2025-07-10
Contact: Jiahao ZU E-mail:matao@nudt.edu.cn;huangjun0111@nudt.edu.cn;jh_zu@stu.xidian.edu.cn;wgli@xidian.edu.cn
About author:
MA Tao was born in 1979. He received his B.S., M.S. and Ph.D. degrees from Electronic Engineering Intitute of PLA, Hefei, China, in 2001, 2005 and 2009, respectively. He is currently an professor with National University of Defense Technology. His research interests include wireless network security and system simulation. E-mail: matao@nudt.edu.cn

HUANG Jun was born in 1983. He received his B.E. degree in automation, M.S. degree in military communication, and Ph.D. degree in information security all from Electronic Engineeoring Institute of PLA. He is an associate professor at National University of Denfense Technology, China. His research interest is wireless network security. E-mail: huangjun0111@nudt.edu.cn

ZU Jiahao was born in 2000. He received his B.S. degree from ShaanXi University of Science Technology, Xi ’an, China. He is currently a master student with the State Key Laboratory of Integrated Services Networks, Xidian University, and the School of Telecommunication Engineering, Xidian University. His research interests include communication technology and massive multiple input multiple output technology. E-mail: jh_zu@stu.xidian.edu.cn

LI Wen’gang was born in 1980. He received his B.S. and Ph.D. degrees in communication and information systems from Xidian University, Xi’an, China, in 2004 and 2010, respectively. He is currently an associate professor with the School of Communication Engineering, Xidian University. His research interests include navigation and positioning, broadband wireless communication, massive multiple input multiple output technology, satellite communications, cognitive radio networks and its application. E-mail: wgli@xidian.edu.cn
Supported by:
This work was supported by the National Natural Science Foundation of China (61901341).

Abstract

Abstract:

Using the existing positioning technology can easily obtain high-precision positioning information, which can save resources and reduce complexity when used in the communication field. In this paper, we propose a location-based user scheduling and beamforming scheme for the downlink of a massive multi-user input-output system. Specifically, we combine an analog outer beamformer with a digital inner beamformer. An outer beamformer can be selected from a codebook formed by antenna steering vectors, and then a reduced-complexity inner beamformer based on iterative orthogonal matrices and right triangular matrices (QR) decomposition is applied to cancel inter-user interference. Then, we propose a low-complexity user selection algorithm using location information in this paper. We first derive the geometric angle between channel matrices, which represent the correlation between users. Furthermore, we derive the asymptotic signal to interference-plus-noise ratio (SINR) of the system in the context of two-stage beamforming using random matrix theory (RMT), taking into account inter-channel correlations and energies. Simulation results show that the algorithm can achieve higher system and speed while reducing computational complexity.

Key words: massive multiple input multiple output, user scheduling, two-stage beamforming, low-complexity

Tao MA, Jun HUANG, Jiahao ZU, Wen’gang LI. Location-driven beamforming for massive multi-user MIMO systems[J]. Journal of Systems Engineering and Electronics, 2025, 36(3): 609-622.

Figures/Tables 11

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Scheme	Complexity
Scheme	Analog precoder	Digital precoder
Proposed	−	$ O({N_S}N_R^2 + N_S^2{N_R}) $
ZF based	−	$ O(N_R^3 + {N_T}N_R^2) $
Typical hybrid	$ O(N_T^2) $	$ O({N_S}N_R^2 + N_S^2{N_R}) $

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Location-driven beamforming for massive multi-user MIMO systems

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