Abstract
Large-scale multiple-input multiple-output (MIMO) system has the advantages of high energy efficiency and spectrum utilization. But using some cheap hardware may cause some problems, such as nonlinearity of the high power amplifier (HPA). When HPA works in the nonlinear region, it will affect the received signal and greatly reduce the performance of the system. In this paper, we first study the impact caused by nonlinear HPA, and then we optimize the traditional precoding algorithm to design an improved precoding algorithm which can reduce the impact. The simulation results show that the proposed algorithms perform better in bit error ratio and system capacity compared to the block of diagonalization (BD) precoding algorithm and forced zero (ZF) precoding algorithm, especially in the condition of high signal to noise ratio (SNR). So we can draw the conclusion that the algorithms proposed in this paper are able to reduce the impact caused by nonlinear HPA to the system.
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Acknowledgments
The research was supported in part by Postdoctoral Research Funding Plan in Jiangsu Province (Grant No. 1501073B), Natural Science Foundation of Nanjing University of Posts and Telecommunications (Grant No. NY214108), Natural Science Foundation of China (NSFC) (Grant No. 61401399), and the Open Research Fund of National Mobile Communications Research Laboratory, Southeast University (Grant No. 2016D05).
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© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Yin, X., Dai, J., Cheng, C., Huang, Z. (2018). Linear Massive MIMO Precoding Based on Nonlinear High-Power Amplifier. In: Gu, X., Liu, G., Li, B. (eds) Machine Learning and Intelligent Communications. MLICOM 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 226. Springer, Cham. https://doi.org/10.1007/978-3-319-73564-1_47
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DOI: https://doi.org/10.1007/978-3-319-73564-1_47
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