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Study of WiFi Signal Propagation and the Location of the Wireless AP WiFi信号传播与无线AP定位研究
Pub Date : 2021-01-01 DOI: 10.12677/HJWC.2021.112004
丽琴 陈
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引用次数: 0
Design of Gateway System for Distributed Control of Electric Bicycle Charging Pile 电动自行车充电桩分布式控制网关系统设计
Pub Date : 2021-01-01 DOI: 10.12677/hjwc.2021.113007
松杰 贺
{"title":"Design of Gateway System for Distributed Control of Electric Bicycle Charging Pile","authors":"松杰 贺","doi":"10.12677/hjwc.2021.113007","DOIUrl":"https://doi.org/10.12677/hjwc.2021.113007","url":null,"abstract":"","PeriodicalId":66606,"journal":{"name":"无线通信","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66096787","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Application and Performance analysis of Cognitive Radio Cooperative Transmission in Internet of Vehicles 认知无线电协同传输在车联网中的应用及性能分析
Pub Date : 2021-01-01 DOI: 10.12677/hjwc.2021.111001
阳 刘
{"title":"Application and Performance analysis of Cognitive Radio Cooperative Transmission in Internet of Vehicles","authors":"阳 刘","doi":"10.12677/hjwc.2021.111001","DOIUrl":"https://doi.org/10.12677/hjwc.2021.111001","url":null,"abstract":"","PeriodicalId":66606,"journal":{"name":"无线通信","volume":"65 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66097014","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Direction Finding of Shortwave Emitters Based on Spectrum Estimation 基于频谱估计的短波发射机测向
Pub Date : 2021-01-01 DOI: 10.12677/hjwc.2021.113006
龙涛 李
针对短波沃森瓦特测向系统,提出了一种基于波束形成的测向算法,该算法将沃森瓦特接收机的三个通道输出进行线性组合,形成阵列测量矢量,采用最小方差无失真波束形成器进行空域滤波测向。与传统沃森瓦特算法相比,该方法充分利用了爱德考克天线的阵列孔径。计算机仿真表明,所提算法的测向精度优于传统算法。 An algorithm based on beamforming is proposed for shortwave direction finding with a Watson- Watt (WW) system. It constructs an array measurement vector by the linear combination of the outputs of the three receiving channels of a WW system, and then utilizes the Minimum Variance Distortionless Response (MVDR) beamforming to perform spatial filtering. Compared to the traditional WW algorithm, the proposed method takes advantage of the full aperture of the Adcock antenna array, which leads to its better accuracy of direction finding, and it has been demonstrated by computer simulations.
针对短波沃森瓦特测向系统,提出了一种基于波束形成的测向算法,该算法将沃森瓦特接收机的三个通道输出进行线性组合,形成阵列测量矢量,采用最小方差无失真波束形成器进行空域滤波测向。与传统沃森瓦特算法相比,该方法充分利用了爱德考克天线的阵列孔径。计算机仿真表明,所提算法的测向精度优于传统算法。 An algorithm based on beamforming is proposed for shortwave direction finding with a Watson- Watt (WW) system. It constructs an array measurement vector by the linear combination of the outputs of the three receiving channels of a WW system, and then utilizes the Minimum Variance Distortionless Response (MVDR) beamforming to perform spatial filtering. Compared to the traditional WW algorithm, the proposed method takes advantage of the full aperture of the Adcock antenna array, which leads to its better accuracy of direction finding, and it has been demonstrated by computer simulations.
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引用次数: 0
A Design of 6G Oriented Broadband Multi-Beam Wireless Communication Prototype System 面向6G的宽带多波束无线通信原型系统设计
Pub Date : 2021-01-01 DOI: 10.12677/hjwc.2021.114013
田 佳辰
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引用次数: 0
Study on CSI Compression and Restoration with Deep Learning in RIS-Assisted MIMO Systems ris辅助MIMO系统中基于深度学习的CSI压缩与恢复研究
Pub Date : 2021-01-01 DOI: 10.12677/hjwc.2021.116015
富铿 黄
Intelligent reflective surfaces (IRS) have been widely studied due to their advantages such as low cost, low power consumption, and ability to improve communication quality. In this paper, an IRS-assisted multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) communication system is considered. In order to improve the performance gain of the system, the user (UE) needs to send its channel state information (CSI) of several channels to the base station (BS) via feedback link. Therefore, the data volume and feedback overhead of CSI in this system will undoubtedly be much huger, as compared to the conventional MIMO systems. To address this problem, we propose an attention-based deep residual network named IARNet (In-ception-Attention-Residual-Net) to compress and reconstruct the CSI with large data volume. The IARNet combines several sub-modules based on the traditional Inception network, such as the multi-convolutional feature fusion module, the hybrid attention module, and the residual module, etc. This hybrid structure can effectively compress and reconstruct the CSI of large data volumes. Simulation results show that with the warm-up training scheme, IARNet can significantly improve the reconstruction quality of CSI of large data volumes, as compared to two existing deep learning networks.
{"title":"Study on CSI Compression and Restoration with Deep Learning in RIS-Assisted MIMO Systems","authors":"富铿 黄","doi":"10.12677/hjwc.2021.116015","DOIUrl":"https://doi.org/10.12677/hjwc.2021.116015","url":null,"abstract":"Intelligent reflective surfaces (IRS) have been widely studied due to their advantages such as low cost, low power consumption, and ability to improve communication quality. In this paper, an IRS-assisted multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) communication system is considered. In order to improve the performance gain of the system, the user (UE) needs to send its channel state information (CSI) of several channels to the base station (BS) via feedback link. Therefore, the data volume and feedback overhead of CSI in this system will undoubtedly be much huger, as compared to the conventional MIMO systems. To address this problem, we propose an attention-based deep residual network named IARNet (In-ception-Attention-Residual-Net) to compress and reconstruct the CSI with large data volume. The IARNet combines several sub-modules based on the traditional Inception network, such as the multi-convolutional feature fusion module, the hybrid attention module, and the residual module, etc. This hybrid structure can effectively compress and reconstruct the CSI of large data volumes. Simulation results show that with the warm-up training scheme, IARNet can significantly improve the reconstruction quality of CSI of large data volumes, as compared to two existing deep learning networks.","PeriodicalId":66606,"journal":{"name":"无线通信","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66097824","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Design and Implementation of Stratospheric Airship Data Transmission System Based on FPGA 基于FPGA的平流层飞艇数据传输系统设计与实现
Pub Date : 2020-01-01 DOI: 10.12677/hjwc.2020.103003
玉梅 赵
{"title":"Design and Implementation of Stratospheric Airship Data Transmission System Based on FPGA","authors":"玉梅 赵","doi":"10.12677/hjwc.2020.103003","DOIUrl":"https://doi.org/10.12677/hjwc.2020.103003","url":null,"abstract":"","PeriodicalId":66606,"journal":{"name":"无线通信","volume":"10 1","pages":"19-27"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66094777","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Discussion on the Testing Technology of ODN in FTTH FTTH中ODN测试技术的探讨
Pub Date : 2020-01-01 DOI: 10.12677/hjwc.2020.106014
兴明 俞
{"title":"Discussion on the Testing Technology of ODN in FTTH","authors":"兴明 俞","doi":"10.12677/hjwc.2020.106014","DOIUrl":"https://doi.org/10.12677/hjwc.2020.106014","url":null,"abstract":"","PeriodicalId":66606,"journal":{"name":"无线通信","volume":"10 1","pages":"101-108"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66096373","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Design of a 16-dB S-Band Attenuator 16db s波段衰减器的设计
Pub Date : 2020-01-01 DOI: 10.12677/hjwc.2020.106011
万里 李
{"title":"Design of a 16-dB S-Band Attenuator","authors":"万里 李","doi":"10.12677/hjwc.2020.106011","DOIUrl":"https://doi.org/10.12677/hjwc.2020.106011","url":null,"abstract":"","PeriodicalId":66606,"journal":{"name":"无线通信","volume":"10 1","pages":"79-83"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66096491","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Application and Implementation of Deep Learning in Wireless Transmission Physical Layer 深度学习在无线传输物理层中的应用与实现
Pub Date : 2020-01-01 DOI: 10.12677/hjwc.2020.101001
君慧 高
{"title":"Application and Implementation of Deep Learning in Wireless Transmission Physical Layer","authors":"君慧 高","doi":"10.12677/hjwc.2020.101001","DOIUrl":"https://doi.org/10.12677/hjwc.2020.101001","url":null,"abstract":"","PeriodicalId":66606,"journal":{"name":"无线通信","volume":"10 1","pages":"1-12"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66094497","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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