地面基地台超載時使用無人機基地台支援之研究

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姓名

林群穎(Chun-Ying Lin) 查詢紙本館藏

畢業系所

通訊工程學系

論文名稱

地面基地台超載時使用無人機基地台支援之研究
(Research on using UAVs to support the overload of terrestrial base station)

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至系統瀏覽論文 (2030-9-23以後開放)

摘要(中)

隨著溫室氣體的排放，極端氣候越來越常發生。面對極端氣候的肆虐，地面
通訊設備會遭遇到嚴厲的挑戰。颱風、海嘯及地震等天然災害都會較以往更加劇烈，容易使通訊設備造成損壞。其它像是停電、使用者數過多等皆會造成當地的網路壅塞。如何應對地面基地台超載而造成的通訊困難是本篇論文的方向。
本篇論文使用無人機基地台(UAVBS)來解決地面一些人口壅塞的地區像是活
動現場等。這些地區的地面基地台容易超載，需要無人機基地台來分擔一些負載。無人機基地台具有機動性，而無人機基地台位置的選擇是一個問題。本篇論文使用了機器學習中的分群方法來選擇無人機基地台的位置，包含了K-means 與DBSCAN (Density-based spatial clustering of applications with noise)。在選擇完無人機基地台的位置後，會探討在人口壅塞的地區在無人機基地台超載時使用調整無人機基地台最大發射功率的方式來改變cell coverage 以此來分攤負載的情形以及無人機基地台間的負載平衡。
由實驗結果顯示使用K-means plus DBSCAN 及調整無人機基地台的最大發射功率能達到更好的負載平衡及精準分配UAVBS 在地面基地台超載地區。

摘要(英)

With the emission of greenhouse gases, extreme weather becomes more and more frequent. In face of extreme weather ravages, communication equipment on the ground will encounter serious challenges. Natural disasters such as typhoons, tsunamis and earthquakes will be more severe than ever, easy to cause damage to communication equipment. Others such as power outages, too many users, etc. will cause regional networks congestion. How to deal with the lack of communication caused by terrestrial base station overload is the direction of my paper.
This paper uses unmanned aerial vehicle base station (UAVBS) to solve some of the population congestion areas on the ground, campaign etc. Terrestrial base stations in these areas are easy to overload, and the UAVBSs are needed to s
hare some of the load. The UAVBS has the mobility, and the choice of the location of the UAV base station is a problem. This paper uses the grouping method in machine learning to select the location of the UAVBSs, including K-means and DBSCAN (Density-based spatial clustering of applications with noise). After selecting the location of the UAVBS, this paper will analyze the condition of adjusting UAVBS maximum transmit power to change cell coverage while UAVBSs
overload on crowded area and analyze the load balancing between UAVBSs.
Experiment results show using K-means plus DBSCAN and adjusting UAVBS maximum transmit power can get better load balancing and precisely arrange UAVBS on terrestrial base station overload area.

關鍵字(中)

★ 無人機基地台
★ 地面基地台
★ 負載平衡

關鍵字(英)

★ K-means
★ DBSCAN

論文目次

中文摘要...I
英文摘要...II
誌謝...III
目錄...IV
圖目錄...VII
表目錄...X
第一章序論...1
1-1 前言...1
1-2 研究動機...1
1-3 論文架構...2
第二章相關研究背景...3
2-1 LTE (Long Term Evolution) ...3
2-1-1 LTE 相關技術...3
2-1-2 LTE 系統架構...4
2-1-3 LTE 實體層資源分配...6
2-2 異質網路(Heterogeneous Network) ...8
2-3 UAV (Unmanned Aerial Vehicle) ...10
2-3-1 UAS (Unmanned Aerial System) ...10
2-3-2 UAV 中繼傳輸...11
2-4 機器學習(ML) ...12
2-4-1 機器學習運作流程...12
2-4-2 機器學習類別...13
2-4-3 K-means 演算法...15
2-4-4 DBSCAN...17
2-4-5 UAV path loss 公式...18
第三章系統架構與研究方法...19
3-1 系統架構與情境...19
3-2 系統流程與演算法...21
3-2-1 以K-means 來取得UAVBS 位置...22
3-2-2 以K-means plus DBSCAN 來取得UAVBS 位置...26
3-2-3 額外調整UAVBS 位置的方法...30
3-2-4 以K-means plus DBSCAN plus thrust 來取得UAVBS 位
置...30
3-2-5 以K-means plus DBSCAN plus suction 來取得UAVBS
位置...32
3-2-6 調整UAVBS 最大發射功率的方式...34
3-2-7 調整UAVBS 高度的方式...35
第四章模擬與分析...38
4-1 模擬參數:...38
4-2 使用K-means plus DBSCAN 產生的服務數量差別...39
4-3 調整UAVBS 最大發射功率的效果...43
4-4 K-means plus DBSCAN plus thrust 適合的情境...51
4-5 K-means plus DBSCAN plus suction 適合的情境...52
第五章結論與未來研究方向...55
參考文獻...56

參考文獻

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指導教授

吳中實(Jung-Shyr Wu)

審核日期

2022-9-26

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