{"title":"基于卷积神经网络的无许可频谱D2D通信发射功率控制","authors":"Zhenyu Fan, Xinyu Gu","doi":"10.1109/IC-NIDC54101.2021.9660479","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a means of Device-to-Device communication extended to unlicensed spectrum (D2D-U) to alleviate the dense deployment of smart devices in licensed spectrum with consideration of fairly coexisting with Wi-Fi. To achieve high system performance in D2D-U, a method of managing D2D mutual interference is needed. For this issue, we propose a convolutional neural network (CNN)-based transmit power control scheme which experiences a low computational complexity compared with conventional transmit power control scheme. Simulation results indicate that the CNN-based power control scheme can achieve superior performance with a low computational complexity.","PeriodicalId":264468,"journal":{"name":"2021 7th IEEE International Conference on Network Intelligence and Digital Content (IC-NIDC)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Convolutional Neural Network Based Transmit Power Control for D2D Communication in Unlicensed Spectrum\",\"authors\":\"Zhenyu Fan, Xinyu Gu\",\"doi\":\"10.1109/IC-NIDC54101.2021.9660479\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose a means of Device-to-Device communication extended to unlicensed spectrum (D2D-U) to alleviate the dense deployment of smart devices in licensed spectrum with consideration of fairly coexisting with Wi-Fi. To achieve high system performance in D2D-U, a method of managing D2D mutual interference is needed. For this issue, we propose a convolutional neural network (CNN)-based transmit power control scheme which experiences a low computational complexity compared with conventional transmit power control scheme. Simulation results indicate that the CNN-based power control scheme can achieve superior performance with a low computational complexity.\",\"PeriodicalId\":264468,\"journal\":{\"name\":\"2021 7th IEEE International Conference on Network Intelligence and Digital Content (IC-NIDC)\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-11-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 7th IEEE International Conference on Network Intelligence and Digital Content (IC-NIDC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IC-NIDC54101.2021.9660479\",\"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 7th IEEE International Conference on Network Intelligence and Digital Content (IC-NIDC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IC-NIDC54101.2021.9660479","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Convolutional Neural Network Based Transmit Power Control for D2D Communication in Unlicensed Spectrum
In this paper, we propose a means of Device-to-Device communication extended to unlicensed spectrum (D2D-U) to alleviate the dense deployment of smart devices in licensed spectrum with consideration of fairly coexisting with Wi-Fi. To achieve high system performance in D2D-U, a method of managing D2D mutual interference is needed. For this issue, we propose a convolutional neural network (CNN)-based transmit power control scheme which experiences a low computational complexity compared with conventional transmit power control scheme. Simulation results indicate that the CNN-based power control scheme can achieve superior performance with a low computational complexity.