Hybrid Beamforming for Multi User Massive MIMO Systems

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Abdirahman Abdikarim Hussein
Asst.Prof.Didem Kıvanç Türeli


The increasing demand in wireless communications for enhanced spectral efficiency (SE) and throughput makes massive multiple input multiple output (MIMO) a great choice for meeting those demands by using a vast set of antennas. Despite the advantages of massive MIMO, to implement such systems comes with a huge price tag and consumes a lot of power. Hybrid beamforming (HBF) architecture has drawn considerable attention in the past few years, by significantly decreasing the amount of employed radio frequency (RF) chains and combining high dimensional analog beamforming (ABF) using phase shifters (PS) together with low dimensional digital beamforming (DBF). However, because of the extreme energy consumption and hardware complexity, traditional precoding designs are difficult to implement. In this paper, two HBF techniques are proposed to address the above issue. (i) low complexity precoding known as phased zero forcing (PZF) precoding, which controls phase only in the RF domain (ii) singular value decomposition (SVD) based optimal unconstrained precoding, that can be implemented on inexpensive RF components.

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How to Cite
Hussein, A. A., & Kıvanç Türeli, D. . (2023). Hybrid Beamforming for Multi User Massive MIMO Systems . Orclever Proceedings of Research and Development, 2(1), 50–58. https://doi.org/10.56038/oprd.v2i1.246


Hedi Khammari, Ahmed Musa, “A Survey on Hybrid Beamforming Techniques in 5G: Architecture and System Model Perspectives,” in IEEE Communications Surveys & Tutorials, vol. 20, no. 4, pp. 3060-3097, Fourthquarter 2018. DOI: https://doi.org/10.1109/COMST.2018.2843719

Nuria G. Prelcic, Robert W. Heath, Akbar M. Sayeed, Wonil Roh and Sundeep Rangan, “An Overview of Signal Processing Techniques for Millimeter Wave MIMO Systems,” in IEEE Journal of Selected Topics in Signal Processing, vol. 10, no. 3, pp. 436-453, April 2016. DOI: https://doi.org/10.1109/JSTSP.2016.2523924

Jakob Hoydis, Emil Björnson, and S. Luca, “Massive MIMO Networks: Spectral, Energy, and Hardware Efficiency”, Foundations and Trends R in Signal Processing: Vol. 11, No. 3-4, pp 154–655, 2017. DOI: https://doi.org/10.1561/2000000093

Hongliang Zhang, Boya Di, Vincent H. Poor and Yonghui Li, "Hybrid Beamforming for Reconfigurable Intelligent Surface based Multi-User Communications: Achievable Rates With Limited Discrete Phase Shifts," in IEEE Journal on Selected Areas in Communications, vol. 38, no. 8, pp. 1809-1822, Aug. 2020. DOI: https://doi.org/10.1109/JSAC.2020.3000813

Y. Zhang, et al., "Digital Beamforming-Based Massive MIMO Transceiver for 5G Millimeter-Wave Communications," in IEEE Transactions on Microwave Theory and Techniques, vol. 66, no. 7, pp. 3403-3418, July 2018. DOI: https://doi.org/10.1109/TMTT.2018.2829702

Lingyang Song, Boya Di, Hongliang Zhang, and Zhu Han, "Practical Hybrid Beamforming With Finite-Resolution Phase Shifters for Reconfigurable Intelligent Surface Based Multi-User Communications," in IEEE Transactions on Vehicular Technology, vol. 69, no. 4, pp. 4565-4570, April 2020. DOI: https://doi.org/10.1109/TVT.2020.2973202

Q. Abdullah, A. Salh, N. Shahida, L. Audah "A brief survey and investigation of hybrid beamforming for millimeter waves in 5G massive MIMO systems." arXiv preprint arXiv:2105.00180, 2021.

Xiaoyong Wu, Fangfang Yin, and Danpu Liu, "Hybrid Beamforming for Multi-User Massive MIMO Systems," in IEEE Transactions on Com., vol. 66, no. 9, pp. 3879-3891, Sept. 2018. DOI: https://doi.org/10.1109/TCOMM.2018.2829511

Jing Jiang, Li Zhen and Yue Yuan, "Multi-User Hybrid Precoding for Dynamic Subarrays in mmWave Massive MIMO Systems," in IEEE Access, vol. 7, pp. 101718-101728, 2019. DOI: https://doi.org/10.1109/ACCESS.2019.2929927

Yiwei Song, Guan Gui, Hongji Huang, Fumiyuki Adachi and Jie Yang, "Deep-Learning-Based Millimeter-Wave Massive MIMO for Hybrid Precoding," in IEEE Transactions on Vehicular Technology, vol. 68, no. 3, pp. 3027-3032, March 2019. DOI: https://doi.org/10.1109/TVT.2019.2893928

T. Lin, Jiaqi Cong, Yu Zhu, Khaled B. Letaief and J. Zhang, "Hybrid Beamforming for Millimeter Wave Systems Using the MMSE Criterion," in IEEE Transactions on Communications, vol. 67, no. 5, pp. 3693-3708, May 2019. DOI: https://doi.org/10.1109/TCOMM.2019.2893632

Xiaoshen Song, Giuseppe Caire and Thomas Kühne, "Fully-/Partially-Connected Hybrid Beamforming Architectures for mmWave MU-MIMO," in IEEE Transactions on Wireless Communications, vol. 19, no. 3, pp. 1754-1769, March 2020. DOI: https://doi.org/10.1109/TWC.2019.2957227

Nhan Thanh Nguyen and Kyungchun Lee, "Unequally Sub-Connected Architecture for Hybrid Beamforming in Massive MIMO Systems," in IEEE Transactions on Wireless Communications, vol. 19, no. 2, pp. 1127-1140, Feb. 2020. DOI: https://doi.org/10.1109/TWC.2019.2951174

Omar El Ayach, Shadi Abu-Surra, Robert. W. Heath, and Sridhar R., "Spatially Sparse Precoding in Millimeter Wave MIMO Systems," in IEEE Transactions on Wireless Communications, vol. 13, no. 3, pp. 1499-1513, March 2014. DOI: https://doi.org/10.1109/TWC.2014.011714.130846

Wenyan Ma, Chenhao Qi, Julian Cheng and Zaichen Zhang, "Sparse Channel Estimation and Hybrid Precoding Using Deep Learning for Millimeter Wave Massive MIMO," in IEEE Transactions on Communications, vol. 68, no. 5, pp. 2838-2849, May 2020. DOI: https://doi.org/10.1109/TCOMM.2020.2974457

Le Liang and Wei Xu, "Low-complexity hybrid precoding in massive mulituser MIMO systems," IEEE Wireless Communications Letters, vol. 3, no. 6, pp. 653-656, December 2014. DOI: https://doi.org/10.1109/LWC.2014.2363831

Xianru Liu, Shu Cao, Qingyong Deng, "Hybrid Precoding for Massive mmWave MIMO Systems," in IEEE Access, vol. 7, pp. 33577-33586, 2019. DOI: https://doi.org/10.1109/ACCESS.2019.2903166