电工技术学报  2023, Vol. 38 Issue (13): 3400-3412    DOI: 10.19595/j.cnki.1000-6753.tces.220721
电工理论 |
基于双接口分集和数据样本的脉冲噪声抑制算法
陈智雄1,2, 张志坤1, 赵雄文1,2
1.华北电力大学电气与电子工程学院 保定 071003;
2.河北省电力物联网技术重点实验室 保定 071003
An Impulse Noise Suppression Algorithm Based on Dual Interface Diversity and Data Samples
Chen Zhixiong1,2, Zhang Zhikun1, Zhao Xiongwen1,2
1. School of Electrical & Electronic Engineering North China Electric Power University Baoding 071003 China;;
2. Hebei Key Laboratory of Power Internet of Things Technology Baoding 071003 China
全文: PDF (3671 KB)   HTML
输出: BibTeX | EndNote (RIS)      
摘要 针对电力线与无线双接口通信中的电力线突发脉冲噪声(BIN)的干扰问题,提出一种基于分集信号抵消和自适应阈值估计(DSC-ATE)的BIN抑制算法。首先,利用电力线和无线并行信道传输相同的分集信号,接收端通过分集信号抵消获得脉冲噪声样本,降低峰平比对阈值估计的影响;然后利用噪声样本对非线性函数的最佳阈值进行估计;最后对脉冲噪声进行抑制处理。为了提高算法的鲁棒性和可扩展性,该文通过引入折扣因子和学习率来实现算法在复杂度和精度之间的有效折中。与已有的非线性处理算法相比,该方法不需要噪声的先验统计信息,并可根据信道环境的变化自适应地调整阈值。仿真结果表明,所提算法在可靠性和阈值精度方面均具有显著提升。
服务
把本文推荐给朋友
加入我的书架
加入引用管理器
E-mail Alert
RSS
作者相关文章
陈智雄
张志坤
赵雄文
关键词 双接口通信突发脉冲噪声数据样本最佳阈值    
Abstract:Hybrid power line and wireless communication has wide application prospect in the Internet of Things. How to suppress the pulse noise of the power line channel in dual interface communication and improve the reliability of communication system is one of the key problems to be solved urgently. Aiming at the interference problem of power line burst pulse noise (BIN) in the power line and wireless dual interface communication, this paper put forward a BIN suppression algorithm based on diversity signal cancellation and adaptive threshold estimation (DSC-ATE), by using the independence and difference of power line and wireless channel and the consistency of diversity signal. In DSC-ATE, the wireless channel is used to assist the power line channel to extract the noise samples, and then the pulse noise threshold is estimated adaptively through the noise samples, finally the pulse noise is separated from the received signal.
The traditional OFDM system has the problem of peak-to-flat ratio PAPR, which is difficult to obtain the position information of pulse noise directly in the power line channel. Based on the dual-interface communication architecture, a noise sample extraction method based on diversity signal cancellation is proposed, which improves the accuracy of noise detection and can be applied to the optimal threshold prediction. The simulation results show that after diversity signal cancellation, the effect of PAPR is minimal because only background interference remains, and the precise position information of impulse noise can be obtained by using nonlinear transformation, which provides data support for the optimal threshold estimation algorithm.
Secondly, the sample space of impulse noise is constructed by means of signal cancellation processing in diversity transmission, in which the noise data of low SNR ensures the diversity of samples. Then, an optimal threshold estimation algorithm based on noise sample data and nonlinear functions is proposed, which can minimize the bit error rate of the communication system and does not require the prior information of impulse noise. The simulation result shows that the performance of threshold precision, transmission rate, and bit error rate under different SNRs of the algorithm is superior to the traditional algorithms such as the weighted combination criterion (WCC) and siegert criterion (SC). The proposed algorithm also has certain robustness and robustness under different channel fading and noise parameters.
Finally, aiming at the problem of pulse noise elimination in non-stationary environment, the noise threshold is iteratively estimated by using the data sample and the objective function minimization/maximization algorithm, so as to determine the location information of the pulse noise. The convergence rate of the algorithm is adjusted by importing parameters such as learning rate and discount factor, and the threshold can be dynamically adjusted according to the changes of the environment, so as to achieve the effective compromise between the robustness and convergence rate of the algorithm. The simulation result shows that when the learning rate of the algorithm is fixed, the larger the data sample length is, the smaller and more stable the threshold fluctuation is. However, the large data sample length will increase the computational burden, storage burden, and data sample acquisition time, which slow down the update speed of the threshold. In the future, the proposed algorithm DSC-ATE can be combined with sparse theory and compressed sensing for other noise models such as narrowband noise, to further improve the universality of the algorithm.
Key wordsDual interface communication    burst impulse noise    data samples    optimal threshold   
收稿日期: 2022-05-04     
PACS: TM73  
  TN91.6  
基金资助:国家自然科学基金(61601182)和中央高校科研业务费专项资金(2021MS070)资助项目
通讯作者: 陈智雄 男,1983年生,副教授,硕士生导师,研究方向为物联网技术、电力系统通信。E-mail:zxchen@ncepu.edu.cn   
作者简介: 张志坤 男,1995年生,硕士研究生,研究方向为电力系统通信。E-mail:zkzhang@ncepu.edu.cn
引用本文:   
陈智雄, 张志坤, 赵雄文. 基于双接口分集和数据样本的脉冲噪声抑制算法[J]. 电工技术学报, 2023, 38(13): 3400-3412. Chen Zhixiong, Zhang Zhikun, Zhao Xiongwen. An Impulse Noise Suppression Algorithm Based on Dual Interface Diversity and Data Samples. Transactions of China Electrotechnical Society, 2023, 38(13): 3400-3412.
链接本文:  
https://dgjsxb.ces-transaction.com/CN/10.19595/j.cnki.1000-6753.tces.220721          https://dgjsxb.ces-transaction.com/CN/Y2023/V38/I13/3400