Symbol detection aided channel prediction in fast-varying massive MIMO systems: Framework and performance analysis

IF 1.5 4区 计算机科学 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC
Wei Gao, Junqiang Xiao, Chuan Liu, Wei Peng
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引用次数: 0

Abstract

The channel in massive multiple-input multiple-output systems is fast-varying that the pilot signal needs to be sent frequently. To obtain timely channel state information with less pilot overheads, a symbol detection aided channel prediction scheme is proposed in this paper. Then, the prediction error lower bound of the proposed scheme within one interval of effective prediction is analysed. Besides, the approximate close-form post-processing signal to noise ratio is derived for zero-forcing detector with imperfect channel predictions. Numerical simulations are implemented to verify the validity of theoretical analysis. The results show that the theoretical expressions have a close match with the real simulated performance under various simulation parameter settings. In addition, the frequency of transmitting the pilot signals can be significantly reduced when adopting this proposed method. Moreover, the application of the proposed scheme can be further expanded when combining it with channel coding, thereby greatly improving the spectrum efficiency of the system.

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来源期刊
IET Communications
IET Communications 工程技术-工程:电子与电气
CiteScore
4.30
自引率
6.20%
发文量
220
审稿时长
5.9 months
期刊介绍: IET Communications covers the fundamental and generic research for a better understanding of communication technologies to harness the signals for better performing communication systems using various wired and/or wireless media. This Journal is particularly interested in research papers reporting novel solutions to the dominating problems of noise, interference, timing and errors for reduction systems deficiencies such as wasting scarce resources such as spectra, energy and bandwidth. Topics include, but are not limited to: Coding and Communication Theory; Modulation and Signal Design; Wired, Wireless and Optical Communication; Communication System Special Issues. Current Call for Papers: Cognitive and AI-enabled Wireless and Mobile - https://digital-library.theiet.org/files/IET_COM_CFP_CAWM.pdf UAV-Enabled Mobile Edge Computing - https://digital-library.theiet.org/files/IET_COM_CFP_UAV.pdf
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