Hybrid Precoding Algorithm for Millimeter-Wave Massive MIMO Systems with Subconnection Structures
In mmWave massive MIMO systems, traditional digital precoding is difficult to be implemented because of the high cost and energy consumption of RF chains. Fortunately, the hybrid precoding which combines digital precoding and analog precoding not only solves this problem successfully, but also impro...
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| Vydáno v: | Wireless communications and mobile computing Ročník 2021; číslo 1 |
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| Hlavní autoři: | , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Oxford
Hindawi
2021
John Wiley & Sons, Inc |
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| ISSN: | 1530-8669, 1530-8677 |
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| Abstract | In mmWave massive MIMO systems, traditional digital precoding is difficult to be implemented because of the high cost and energy consumption of RF chains. Fortunately, the hybrid precoding which combines digital precoding and analog precoding not only solves this problem successfully, but also improves the performance of the system effectively. However, due to the constant mode constraint introduced by the phase shifter in the analog domain, it is difficult to solve the hybrid precoding directly. There is a solution which divides the total optimization problem into two stages to solve, that is, first fix the digital precoding matrix, solve the analog precoding matrix, and then optimize the digital precoding matrix according to the obtained analog precoding matrix. In this paper, a high energy-efficient hybrid precoding scheme is proposed for the subconnection structure. In the first stage, the optimization problem can be decomposed into a series of subproblems by means of the independent submatrix structure of the analog precoding matrix. When the optimized analog precoding matrix is obtained, the digital precoding matrix can be solved by the minimum mean error (MMSE). Finally, the digital precoding matrix is normalized to satisfy the constraint conditions. The simulation results demonstrate that the performance of the proposed algorithm is close to that of fully digital precoding based on subconnection structure and better than that of the existing algorithms. In addition, this paper presents the simulation analysis of the algorithm performance under imperfect channel state information. Simulation results show that when the estimation accuracy of channel state information is 0.8, the spectral efficiency of the proposed algorithm can already be maintained at a good level. |
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| AbstractList | In mmWave massive MIMO systems, traditional digital precoding is difficult to be implemented because of the high cost and energy consumption of RF chains. Fortunately, the hybrid precoding which combines digital precoding and analog precoding not only solves this problem successfully, but also improves the performance of the system effectively. However, due to the constant mode constraint introduced by the phase shifter in the analog domain, it is difficult to solve the hybrid precoding directly. There is a solution which divides the total optimization problem into two stages to solve, that is, first fix the digital precoding matrix, solve the analog precoding matrix, and then optimize the digital precoding matrix according to the obtained analog precoding matrix. In this paper, a high energy-efficient hybrid precoding scheme is proposed for the subconnection structure. In the first stage, the optimization problem can be decomposed into a series of subproblems by means of the independent submatrix structure of the analog precoding matrix. When the optimized analog precoding matrix is obtained, the digital precoding matrix can be solved by the minimum mean error (MMSE). Finally, the digital precoding matrix is normalized to satisfy the constraint conditions. The simulation results demonstrate that the performance of the proposed algorithm is close to that of fully digital precoding based on subconnection structure and better than that of the existing algorithms. In addition, this paper presents the simulation analysis of the algorithm performance under imperfect channel state information. Simulation results show that when the estimation accuracy of channel state information is 0.8, the spectral efficiency of the proposed algorithm can already be maintained at a good level. |
| Author | Zhang, Xue Zhao, Feng |
| Author_xml | – sequence: 1 givenname: Xue surname: Zhang fullname: Zhang, Xue organization: Key Laboratory of Cognitive Ratio and Information ProcessingGuilin University of Electronic TechnologyGuilin 541004Chinagliet.edu.cn – sequence: 2 givenname: Feng orcidid: 0000-0002-5730-2208 surname: Zhao fullname: Zhao, Feng organization: Guangxi Colleges and Universities Key Laboratory of Complex System Optimization and Big Data ProcessingYulin Normal UniversityYulin 537000Chinaylu.edu.cn |
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| Cites_doi | 10.1109/MWC.2014.6812298 10.1109/TWC.2017.2732405 10.1109/SPAWC.2015.7227018 10.1109/TCOMM.2013.090513.120848 10.1109/TMC.2020.2979710 10.1109/ACCESS.2019.2903166 10.1049/ecej:19970204 10.1049/iet-com.2019.0188 10.1109/TKDE.2016.2645212 10.1109/ICCT.2017.8359606 10.1007/s10878-013-9623-y 10.1109/JSTSP.2016.2523903 10.1155/2007/78907 10.1109/TPDS.2013.75 10.1109/WOCC.2017.7929004 10.1109/JSAC.2016.2549418 10.1109/TWC.2018.2874640 10.1109/ICDCS.2012.29 10.1109/MSP.2011.2178495 10.1109/ACSSC.2008.5074786 10.1145/3027488 10.1109/APS.2016.7696210 10.1109/tit.2010.2090255 10.1109/PROC.1984.12959 10.1109/ICCChinaW.2018.8674523 10.1109/49.995521 10.1109/VTCFall.2019.8891597 10.13164/re.2019.0439 10.1109/COMST.2017.2787460 10.1109/mcom.2015.7010533 10.1109/TWC.2014.011714.130846 |
| ContentType | Journal Article |
| Copyright | Copyright © 2021 Xue Zhang and Feng Zhao. Copyright © 2021 Xue Zhang and Feng Zhao. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
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| SubjectTerms | Algorithms Antennas Communication Decomposition Energy consumption Energy efficiency Millimeter waves MIMO (control systems) Optimization Performance enhancement Phase shifters Receivers & amplifiers Simulation |
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| Title | Hybrid Precoding Algorithm for Millimeter-Wave Massive MIMO Systems with Subconnection Structures |
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