高级搜索

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

基于干扰观测的无线通信系统抗干扰功率控制算法

牛英滔 姚行 张凯

牛英滔, 姚行, 张凯. 基于干扰观测的无线通信系统抗干扰功率控制算法[J]. 电子与信息学报, 2023, 45(11): 4033-4040. doi: 10.11999/JEIT230870
引用本文: 牛英滔, 姚行, 张凯. 基于干扰观测的无线通信系统抗干扰功率控制算法[J]. 电子与信息学报, 2023, 45(11): 4033-4040. doi: 10.11999/JEIT230870
NIU Yingtao, YAO Hang, ZHANG Kai. An Anti-jamming Power Control Algorithm for Wireless Communication System Based on Disturbance Observer[J]. Journal of Electronics & Information Technology, 2023, 45(11): 4033-4040. doi: 10.11999/JEIT230870
Citation: NIU Yingtao, YAO Hang, ZHANG Kai. An Anti-jamming Power Control Algorithm for Wireless Communication System Based on Disturbance Observer[J]. Journal of Electronics & Information Technology, 2023, 45(11): 4033-4040. doi: 10.11999/JEIT230870

基于干扰观测的无线通信系统抗干扰功率控制算法

doi: 10.11999/JEIT230870
基金项目: 国家自然科学基金(62371461)
详细信息
    作者简介:

    牛英滔:男,副研究员,硕士生导师,研究方向为认知无线电、信号感知、通信抗干扰技术等

    姚行:男,硕士生,研究方向为通信抗干扰技术、稳定性控制

    张凯:男,工程师,博士,研究方向为通信抗干扰技术

    通讯作者:

    姚行  202212490461@nuist.edu.cn

  • 中图分类号: TN973

An Anti-jamming Power Control Algorithm for Wireless Communication System Based on Disturbance Observer

Funds: The National Natural Science Foundation of China (62371461)
  • 摘要: 在快速变化的干扰环境下,无线通信系统传输可靠性会受到很大影响。为提升快速时变干扰环境下无线通信系统传输的可靠性,该文提出一种基于干扰观测的无线通信系统抗干扰功率控制算法。该算法首先将受到干扰影响的无线通信系统建模为广义稳定性控制系统,并采用干扰观测器生成系统状态受干扰影响的估计值。然后通过利用估计值来预测未来的跟踪误差和稳态的控制输入,优化系统的控制策略以实现对干扰环境的自适应调整。最后仿真结果表明,与传统方法相比,所提算法能够快速响应干扰变化,显著提高系统在快速时变恶意干扰下传输的可靠性,提高了系统对干扰环境的适应能力。
  • 图  1  无线通信系统抗干扰控制模型

    图  2  在某种调制和某种LDPC码下的误码曲线

    图  3  所提方法系统框图

    图  4  随机脉冲干扰下,加入稳定控制与传统的功率自适应通信系统对比图

    图  5  周期脉冲干扰下,加入稳定控制与强化学习算法的对比图

    图  6  3种功率自适应稳定性控制方案的比较

  • [1] 姚富强. 通信抗干扰工程与实践[M]. 2版. 北京: 电子工业出版社, 2012.

    YAO Fuqiang. Communication Anti-Jamming Engineering and Practice[M]. 2nd ed. Beijing: Publishing House of Electronics Industry, 2012.
    [2] 杨正, 郑云, 余月好, 等. 基于自适应功率分裂的协作非正交多址接入无线携能通信网络性能分析[J]. 通信学报, 2023, 44(1): 177–188. doi: 10.11959/j.issn.1000−436x.2023004

    YANG Zheng, ZHENG Yun, YU Yuehao, et al. Performance analysis for cooperative NOMA networks based SWIPT with adaptive power splitting[J]. Journal on Communications, 2023, 44(1): 177–188. doi: 10.11959/j.issn.1000−436x.2023004
    [3] 苏炎荣, 徐卓农, 吴舒辞. 一种功率自适应控制方案在移动自组网的应用[J]. 自动化技术与应用, 2008, 27(11): 60–62. doi: 10.3969/j.issn.1003-7241.2008.11.017

    SU Yanrong, XU Zhuonong, and WU Shuci. A power-adaptive control protocol for MANET[J]. Techniques of Automation and Applications, 2008, 27(11): 60–62. doi: 10.3969/j.issn.1003-7241.2008.11.017
    [4] 苗丽娟, 李锦涛. 无线传感器网络功率自适应控制算法研究[J]. 信息技术与信息化, 2023(6): 214–217. doi: 10.3969/j.issn.1672-9528.2023.06.054

    MIAO Lijuan and LI Jintao. Research on power adaptive control algorithm for wireless sensor network[J]. Information Technology Informatization, 2023(6): 214–217. doi: 10.3969/j.issn.1672-9528.2023.06.054
    [5] 陈文泰. 基于机器学习的蜂窝网络D2D通信频谱分配与功率控制算法研究[D]. [硕士论文], 东南大学, 2019.

    CHEN Wentai. A study on machine learning based spectrum allocation and power control algorithms for D2D communications underlaying cellular networks[D]. [Master dissertation], Southeast University, 2019.
    [6] ZHOU Quan, NIU Yingtao, XIANG Peng, et al. Intra-domain knowledge reuse assisted reinforcement learning for fast anti-jamming communication[J]. IEEE Transactions on Information Forensics and Security, 2023, 18: 4707–4720. doi: 10.1109/TIFS.2023.3284611
    [7] JIA Ruibao, LIU Liu, ZHENG Xufei, et al. Multi-agent deep reinforcement learning for uplink power control in multi-cell systems[C]. 2022 IEEE International Conference on Communications Workshops, Seoul, South, Korea, 2022: 324–330.
    [8] TONG Tingting, SONG Xiaoqin, NIU Yingtao, et al. Stability control of power adaptation in wireless communication system[C]. 2013 International Conference on Mechatronic Sciences, Electric Engineering and Computer, Shenyang, China, 2013: 287–291.
    [9] SONG Xiaoqin, DONG Li, LI Wenfa, et al. Stability control of multi-parameter adaptive wireless communication systems based on multi-Lyapunov function[J]. High Technology Letters, 2017, 23(4): 375–383. doi: 10.3772/j.issn.1006-6748.2017.04.005
    [10] YAN Yunda, YANG Jun, SUN Zhenxing, et al. Non-linear-disturbance-observer-enhanced MPC for motion control systems with multiple disturbances[J]. IET Control Theory & Applications, 2020, 14(1): 63–72. doi: 10.1049/iet-cta.2018.5821
    [11] ZHANG Lu, YANG Jun, LI Shihua, et al. Invariant manifold based output-feedback sliding mode control for systems with mismatched disturbances[J]. IEEE Transactions on Circuits and Systems II:Express Briefs, 2021, 68(3): 933–937. doi: 10.1109/TCSII.2020.3011458
    [12] PANNOCCHIA G and BEMPORAD A. Combined design of disturbance model and observer for offset-free model predictive control[J]. IEEE Transactions on Automatic Control, 2007, 52(6): 1048–1053. doi: 10.1109/TAC.2007.899096
    [13] YANG Jun, ZHENG Weixing, LI Shihua, et al. Design of a prediction-accuracy-enhanced continuous-time MPC for disturbed systems via a disturbance observer[J]. IEEE Transactions on Industrial Electronics, 2015, 62(9): 5807–5816. doi: 10.1109/TIE.2015.2450736
    [14] CHEN Wenhua, BALANCE D J, and GAWTHROP P J. Optimal control of nonlinear systems: A predictive control approach[J]. Automatica, 2003, 39(4): 633–641. doi: 10.1016/S0005-1098(02)00272-8
    [15] LEVANT A. Higher-order sliding modes, differentiation and output-feedback control[J]. International Journal of Control, 2003, 76(9/10): 924–941. doi: 10.1080/0020717031000099029
  • 加载中
图(6)
计量
  • 文章访问数:  413
  • HTML全文浏览量:  218
  • PDF下载量:  84
  • 被引次数: 0
出版历程
  • 收稿日期:  2023-08-08
  • 修回日期:  2023-11-09
  • 网络出版日期:  2023-11-14
  • 刊出日期:  2023-11-28

目录

    /

    返回文章
    返回