完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.author | Wang, Li-Chun | en_US |
dc.contributor.author | Lai, Chuan-Chi | en_US |
dc.contributor.author | Shuai, Hong-Han | en_US |
dc.contributor.author | Lin, Hsin-Piao | en_US |
dc.contributor.author | Li, Chi-Yu | en_US |
dc.contributor.author | Cheng, Teng-Hu | en_US |
dc.contributor.author | Chen, Chiun-Hsun | en_US |
dc.date.accessioned | 2020-10-05T02:01:29Z | - |
dc.date.available | 2020-10-05T02:01:29Z | - |
dc.date.issued | 2019-01-01 | en_US |
dc.identifier.isbn | 978-1-7281-0960-2 | en_US |
dc.identifier.issn | 2166-0069 | en_US |
dc.identifier.uri | http://hdl.handle.net/11536/155260 | - |
dc.description.abstract | Future mobile communication networks require an Aerial Base Station (ABS) with fast mobility and long-term hovering capabilities. At present, unmanned aerial vehicles (UAV) or drones do not have long flight times and are mainly used for monitoring, surveillance, and image post-processing. On the other hand, the traditional airship is too large and not easy to take off and land. Therefore, we propose to develop an "Artificial Intelligence (AI) Drone-Cruiser" base station that can help 5G mobile communication systems and beyond quickly recover the network after a disaster and handle the instant communications by the flash crowd. The drone-cruiser base station can overcome the communications problem for three types of flash crowds, such as in stadiums, parades, and large plaza so that an appropriate number of aerial base stations can be accurately deployed to meet large and dynamic traffic demands. Artificial intelligence can solve these problems by analyzing the collected data, and then adjust the system parameters in the framework of Self-Organizing Network (SON) to achieve the goals of self-configuration, self-optimization, and self-healing. With the help of AI technologies, 5G networks can become more intelligent. This paper aims to provide a new type of service, On-Demand Aerial Base Station as a Service. This work needs to overcome the following live technical challenges: innovative design of drone-cruisers for the long-time hovering, crowd estimation and prediction, rapid 3D wireless channel learning and modeling, 3D placement of aerial base stations and the integration of WiFi front-haul and millimeter wave/WiGig back-haul networks. | en_US |
dc.language.iso | en_US | en_US |
dc.subject | Aerial Base Station | en_US |
dc.subject | Drone-Cruiser | en_US |
dc.subject | Artificial Intelligence | en_US |
dc.subject | Self-Organizing Network | en_US |
dc.subject | 3D Placement | en_US |
dc.subject | Flying Access Point | en_US |
dc.title | Communications and Networking Technologies for Intelligent Drone Cruisers | en_US |
dc.type | Proceedings Paper | en_US |
dc.identifier.journal | 2019 IEEE GLOBECOM WORKSHOPS (GC WKSHPS) | en_US |
dc.citation.spage | 0 | en_US |
dc.citation.epage | 0 | en_US |
dc.contributor.department | 機械工程學系 | zh_TW |
dc.contributor.department | 資訊工程學系 | zh_TW |
dc.contributor.department | 電機工程學系 | zh_TW |
dc.contributor.department | Department of Mechanical Engineering | en_US |
dc.contributor.department | Department of Computer Science | en_US |
dc.contributor.department | Department of Electrical and Computer Engineering | en_US |
dc.identifier.wosnumber | WOS:000554832400237 | en_US |
dc.citation.woscount | 0 | en_US |
顯示於類別: | 會議論文 |