离散b系数调制NFDM系统的人工神经网络均衡器

2021 13th International Conference on Communication Software and Networks (ICCSN) Pub Date : 2021-06-04 DOI:10.1109/ICCSN52437.2021.9463616

Yingrong Chen, Xi Fang, Qian Liao, Lei Zhang

{"title":"离散b系数调制NFDM系统的人工神经网络均衡器","authors":"Yingrong Chen, Xi Fang, Qian Liao, Lei Zhang","doi":"10.1109/ICCSN52437.2021.9463616","DOIUrl":null,"url":null,"abstract":"In this paper, we established a mathematical model for noise interference in discrete b-coefficients modulated nonlinear frequency division multiplexing (NFDM) system. Based on this model, through a reasonable design of input and output, we proposed a novel artificial neural network (ANN) model as equalizer to suppress noise. As shown in numerical simulation, the anti-noise ability of the discrete b-coefficients modulated NFDM system has been significantly improved by using the proposed ANN equalizer.","PeriodicalId":263568,"journal":{"name":"2021 13th International Conference on Communication Software and Networks (ICCSN)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Artificial Neural Network Equalizer for Discrete B-coefficients Modulated NFDM System\",\"authors\":\"Yingrong Chen, Xi Fang, Qian Liao, Lei Zhang\",\"doi\":\"10.1109/ICCSN52437.2021.9463616\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we established a mathematical model for noise interference in discrete b-coefficients modulated nonlinear frequency division multiplexing (NFDM) system. Based on this model, through a reasonable design of input and output, we proposed a novel artificial neural network (ANN) model as equalizer to suppress noise. As shown in numerical simulation, the anti-noise ability of the discrete b-coefficients modulated NFDM system has been significantly improved by using the proposed ANN equalizer.\",\"PeriodicalId\":263568,\"journal\":{\"name\":\"2021 13th International Conference on Communication Software and Networks (ICCSN)\",\"volume\":\"38 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-06-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 13th International Conference on Communication Software and Networks (ICCSN)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCSN52437.2021.9463616\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 13th International Conference on Communication Software and Networks (ICCSN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCSN52437.2021.9463616","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 0

摘要

本文建立了离散b系数调制非线性频分复用(NFDM)系统噪声干扰的数学模型。在此模型的基础上，通过合理的输入输出设计，提出了一种新的人工神经网络(ANN)模型作为均衡器来抑制噪声。数值模拟结果表明，采用该均衡器后，离散b系数调制NFDM系统的抗噪能力得到了显著提高。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Artificial Neural Network Equalizer for Discrete B-coefficients Modulated NFDM System

In this paper, we established a mathematical model for noise interference in discrete b-coefficients modulated nonlinear frequency division multiplexing (NFDM) system. Based on this model, through a reasonable design of input and output, we proposed a novel artificial neural network (ANN) model as equalizer to suppress noise. As shown in numerical simulation, the anti-noise ability of the discrete b-coefficients modulated NFDM system has been significantly improved by using the proposed ANN equalizer.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

2021 13th International Conference on Communication Software and Networks (ICCSN)

自引率

0.00%

发文量