完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.author | Wu, Chu-Peng | en_US |
dc.contributor.author | Li, Yun-Ruei | en_US |
dc.contributor.author | Wang, Jing-Ling | en_US |
dc.contributor.author | Lin, Hsin-Piao | en_US |
dc.contributor.author | Wang, Li-Chun | en_US |
dc.contributor.author | Jeng, Shiann-Shiun | en_US |
dc.contributor.author | Chen, Jen-Yeu | en_US |
dc.date.accessioned | 2020-10-05T02:00:32Z | - |
dc.date.available | 2020-10-05T02:00:32Z | - |
dc.date.issued | 2020-01-01 | en_US |
dc.identifier.isbn | 978-1-7281-3893-0 | en_US |
dc.identifier.issn | 2331-9852 | en_US |
dc.identifier.uri | http://hdl.handle.net/11536/155061 | - |
dc.description.abstract | Recently, the development of Unmanned Aerial Vehicle (UAV) has been nearly matured and widely used in various fields. The combination of UAV and communication technologies, such as UAV Base Station (UAV-BS), can significantly increase the flexibility and scalability of the overall communication networks to provide more efficient communication services. While the UAVBS improves the network service efficiency, the quality of services (QoS) in the air-to-ground communication link is highly affected unless the right users are unknown. In this paper, we propose the learning-based downlink user selection algorithm. The 3D downlink channel can be fast identified to judiciously select the users subset. In our proposed framework, we combine the k-means clustering and Convolutional Neural Network (CNN) that can increase the estimation accuracy of 3D wireless channels to enhance the communication service efficiency of the UAV-BS network. The field measurement results show that proposed method can achieve an average bit error rate (BER) of 3.56x 10(-7), which is better than the distance-based selection scheme that has an average of BER 2.88x10(-3). The feasibility and effectiveness of the proposed method in real environment are proved, experimentally. | en_US |
dc.language.iso | en_US | en_US |
dc.title | Learning-based Downlink User Selection Algorithm for UAV-BS Communication Network | en_US |
dc.type | Proceedings Paper | en_US |
dc.identifier.journal | 2020 IEEE 17TH ANNUAL CONSUMER COMMUNICATIONS & NETWORKING CONFERENCE (CCNC 2020) | en_US |
dc.citation.spage | 0 | en_US |
dc.citation.epage | 0 | en_US |
dc.contributor.department | 電子工程學系及電子研究所 | zh_TW |
dc.contributor.department | Department of Electronics Engineering and Institute of Electronics | en_US |
dc.identifier.wosnumber | WOS:000544236100069 | en_US |
dc.citation.woscount | 2 | en_US |
顯示於類別: | 會議論文 |