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基于有界成分分析的带内全双工数字自干扰抵消

唐燕群 马伟峰 褚建军 魏玺章

唐燕群, 马伟峰, 褚建军, 魏玺章. 基于有界成分分析的带内全双工数字自干扰抵消[J]. 电子与信息学报, 2023, 45(5): 1619-1626. doi: 10.11999/JEIT220308
引用本文: 唐燕群, 马伟峰, 褚建军, 魏玺章. 基于有界成分分析的带内全双工数字自干扰抵消[J]. 电子与信息学报, 2023, 45(5): 1619-1626. doi: 10.11999/JEIT220308
TANG Yanqun, MA Weifeng, CHU Jianjun, WEI Xizhang. Digital Self-Interference Cancellation Based on Bounded Component Analysis for In-Band Full-Duplex[J]. Journal of Electronics & Information Technology, 2023, 45(5): 1619-1626. doi: 10.11999/JEIT220308
Citation: TANG Yanqun, MA Weifeng, CHU Jianjun, WEI Xizhang. Digital Self-Interference Cancellation Based on Bounded Component Analysis for In-Band Full-Duplex[J]. Journal of Electronics & Information Technology, 2023, 45(5): 1619-1626. doi: 10.11999/JEIT220308

基于有界成分分析的带内全双工数字自干扰抵消

doi: 10.11999/JEIT220308
基金项目: 广东省基础与应用基础研究基金(2019A1515011622),国家自然科学基金(62071499)
详细信息
    作者简介:

    唐燕群:男,副教授,主要研究方向为全双工通信、网络通信安全

    马伟峰:男,硕士生,研究方向为无线通信

    褚建军:男,硕士生,研究方向为无线通信

    魏玺章:男,教授,主要研究方向为雷达目标识别、新体制抗干扰雷达信号设计

    通讯作者:

    魏玺章 weixzh7@mail.sysu.edu.cn

  • 中图分类号: TN925.1

Digital Self-Interference Cancellation Based on Bounded Component Analysis for In-Band Full-Duplex

Funds: Guangdong Natural Science Foundation (2019A1515011622), The National Natural Science Foundation of China (62071499)
  • 摘要: 凭借能够提升频谱利用率的优势,带内全双工(In-Band Full Duplex, IBFD)技术有望成为现代无线通信系统的潜在方案。然而,在应用过程中却面临自干扰抵消(Self-Interference Cancellation, SIC)的巨大挑战。SIC可以从空域、模拟域和数字域3个方面来单独或组合实现。该文重点研究了IBFD数字SIC。针对传统数字SIC性能受到收发链路器件非理想因素限制的问题,该文建立了一种射频辅助链路的IBFD系统,利用有用信号和自干扰信号的有界性,设计了一种基于有界成分分析的数字SIC方法。在视距(Line Of Sight, LOS)和非视距(Non-Line Of Sight, NLOS)两种信道场景下,利用仿真和实测数据进行了验证分析。结果表明,相比较于最小二乘方法和独立成分分析方法,所提有界成分分析方法改善了SIC效果,并提高了系统误码率性能。
  • 图  1  带内全双工收发链路框图

    图  2  有界成分分析原理框图

    图  3  理论数据下不同方法的性能关系

    图  4  实测数据下不同方法的性能关系

    表  1  系统参数设置

    系统参数数值
    自干扰噪声比(dB)30
    调制方式QPSK
    样本长度1000
    底部噪声功率(dBm)–90
    仿真多径数3
    下载: 导出CSV
  • [1] 郝越凡. 同时同频全双工数字域深度学习自干扰抑制技术研究[D]. [硕士论文], 电子科技大学, 2020.

    HAO Yuefan. Full-duplex digital self-interference cancellation based on deep learning[D]. [Master dissertation], University of Electronic Science and Technology of China, 2020.
    [2] ERDEM M, GURBUZ O, and OZKAN H. A residual scheme for digital self-interference cancellation in full duplex communication[C]. 2020 IEEE International Conference on Communications Workshops (ICC Workshops), Dublin, Ireland, 2020: 1–6.
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    [5] HE Meng and HUANG Chuan. Self-interference cancellation for full-duplex massive MIMO OFDM with single RF chain[J]. IEEE Wireless Communications Letters, 2020, 9(1): 26–29. doi: 10.1109/LWC.2019.2940433
    [6] LEE D and MIN B W. Demonstration of self-interference antenna suppression and RF cancellation for full duplex MIMO communications[C]. 2020 IEEE Wireless Communications and Networking Conference Workshops (WCNCW), Seoul, Korea (South), 2020: 1–4.
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    DONG Fangliang. Research on self-interference suppression algorithms in simultaneous transceiver system[D]. [Master dissertation], Xidian Universtioity, 2019.
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    [13] HUANGFU Yafan, LIU Youjiang, ZHANG Qi, et al. Nonlinear digital self-interference cancellation for full duplex systems in frequency agility mode[C]. 2019 IEEE 19th International Conference on Communication Technology, Xi'an, China, 2019: 16–19.
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    SU Qiao, SHEN Yuehong, and XU Pengcheng. Fast separation algorithm for bounded mixed signals[J]. Computer Engineering, 2016, 42(2): 86–92. doi: 10.3969/j.issn.1000-3428.2016.02.016
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出版历程
  • 收稿日期:  2022-03-22
  • 修回日期:  2022-11-14
  • 网络出版日期:  2022-11-17
  • 刊出日期:  2023-05-10

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