Pub Date : 2021-01-01DOI: 10.12677/HJWC.2021.112004
丽琴 陈
{"title":"Study of WiFi Signal Propagation and the Location of the Wireless AP","authors":"丽琴 陈","doi":"10.12677/HJWC.2021.112004","DOIUrl":"https://doi.org/10.12677/HJWC.2021.112004","url":null,"abstract":"","PeriodicalId":66606,"journal":{"name":"无线通信","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66096906","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}
Pub Date : 2021-01-01DOI: 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":null,"pages":null},"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}
Pub Date : 2021-01-01DOI: 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":null,"pages":null},"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}
Pub Date : 2021-01-01DOI: 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.
{"title":"Direction Finding of Shortwave Emitters Based on Spectrum Estimation","authors":"龙涛 李","doi":"10.12677/hjwc.2021.113006","DOIUrl":"https://doi.org/10.12677/hjwc.2021.113006","url":null,"abstract":"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.","PeriodicalId":66606,"journal":{"name":"无线通信","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66096714","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}
Pub Date : 2021-01-01DOI: 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":null,"pages":null},"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}
Pub Date : 2020-01-01DOI: 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":null,"pages":null},"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}
Pub Date : 2020-01-01DOI: 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":null,"pages":null},"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}
Pub Date : 2020-01-01DOI: 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":null,"pages":null},"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}
Pub Date : 2020-01-01DOI: 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":null,"pages":null},"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}
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