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以作者查詢圖書館館藏 、以作者查詢臺灣博碩士 、以作者查詢全國書目 、勘誤回報 、線上人數：97 、訪客IP：18.190.153.213
姓名 羅鎮元(Zhen-Yuan Lo) 查詢紙本館藏 畢業系所 通訊工程學系 論文名稱 以機器學習方法動態調整無人機基地台的負載平衡之研究
(The study of Dynamically Adjusting Load Balance of UAV Base Station by Machine Learning)檔案 [Endnote RIS 格式]
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至系統瀏覽論文 ( 永不開放)
摘要(中) 當基地台無法提供服務的時候，為維持該區域的通訊狀況，需要盡快的恢復通訊服務，得以對外取得連結。而大量的使用者湧入某個基地台的服務範圍內的時候，導致的基地台的負載不均問題，可能造成某些使用者沒有辦法獲得通訊的服務。
而環境中負載不平衡的問題，存在於基地台與流動使用者之間的位置。當使用者不均勻地分散在環境中會使得負載不平衡，在流動的使用者中有可能讓負載不均的問題更加嚴重。
在本研究裡，我們透過派遣可在空中移動的無人機作為通訊基地台，無人機可以在短時間內快速派遣，克服地形崎嶇的限制和避免進入災區可能再度造成的危險。以使用者的位置為考量配置無人機基地台提供通訊服務，並透過機器學習的方式動態調整無人機的位置，希望能改善在環境中使用者的位置不均勻分散造成某些基地台的負載過重，以達成負載平衡改善的目的。
根據模擬結果，本文提出的動態調整無人機基地台的方法能改善負載不平衡的問題。摘要(英) When the base station is unable to provide services, in order to maintain the communication status of the area, it is necessary to restore the communication service as soon as possible, so that the link can be obtained externally.When a large number of users flood into the service area of a certain base station, the uneven load on the base station may cause some users to have no way to obtain communication services.
The problem of load imbalance in the environment exists between the base station and the mobile user.When the user is unevenly dispersed in the environment, the load is unbalanced, and the problem of uneven load may be more serious among the flowing users.
In this study, we dispatched drones that can be moved in the air as communication base stations. UAVs can be dispatched quickly in a short period of time, overcoming the rugged terrain and avoiding the dangers that may arise again in the disaster area.The UAV base station is configured to provide communication services based on the user′s location, and the position of the UAV is dynamically adjusted through machine learning. It is hoped that the uneven distribution of users in the environment will cause the base station to be overloaded.To achieve the goal of load balancing improvement.
According to the simulation results, the method of dynamically adjusting the UAV base station proposed in this paper can improve the load imbalance.
關鍵字(中) ★ 無人機
★ 通訊基地台
★ 機器學習
★ 負載平衡關鍵字(英) ★ drone
★ communication base station
★ machine learning
★ load balancing論文目次 摘要................................................................................................................I
ABSTRACT..................................................................................................II
誌謝.............................................................................................................III
目錄.............................................................................................................IV
圖目錄........................................................................................................VI
表目錄......................................................................................................VIII
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 長期演進技術(LTE)介紹…...................................................................3
2.1.1 LTE相關技術…..................................................................................3
2.1.2 LTE系統架構…..................................................................................4
2.1.3 LTE協定架構…..................................................................................5
2.1.4 LTE實體層資源規劃…......................................................................7
2.2 基地台相關介紹…................................................................................8
2.3 換手機制…..........................................................................................10
2.4移動模型(Mobility Model) ..................................................................11
2.5無人飛行載具(UAV) ….......................................................................12
2.5.1 UAV無線通訊控制….......................................................................12
2.5.2 UAV無線通訊架構….......................................................................13
2.5.3 UAV中繼傳輸方法….......................................................................14
2.6 機器學習介紹......................................................................................16
2.6.1 機器學習分類…...............................................................................16
2.6.2 K-mean演算法…..............................................................................17
第三章 系統架構與研究方法…...............................................................20
3.1 系統架構與情境..................................................................................20
3.2 系統流程圖與演算法..........................................................................21
第四章 模擬與分析...................................................................................27
4.1 模擬環境與參數設定..........................................................................27
4.2 模擬結果與分析..................................................................................29
第五章 結論與未來研究...........................................................................37
參考文獻.....................................................................................................38
參考文獻 〔1〕3GPP LTE Release 8 and Release 9
〔2〕3GPP TS 23.401 V9.3.0. General Packet Radio Service (GPRS) enhancements for Evolved Universal Terrestrial Radio Access Network(E-UTRAN) access
〔3〕3GPP, TS 36.300 V10.4.0, Evolved Universal Terrestrial Radio Access (E-UTRA) and Evolved Universal Terrestrial Radio Access Network (E-UTRAN); Overall description; Stage 2(Release 10)
〔4〕3GPP TS36.300. Evolved Universal Terrestrial Radio Access
(E-UTRA) and Evolved Universal Terrestrial Radio Access Network(E-UTRAN); Overall description; Stage 2
〔5〕J. Zyren, “Overview of the 3GPP Long Term Evolution Physical Layer,” 3GPPEVOLUTIONWP Rev, July. 2007
〔6〕Damnjanovic, A. ; Montojo, J.; Yongbin Wei ; Tingfang Ji ;Tao Luo ; Vajapeyam, M. ; Taesang Yoo ; Osok Song ;Malladi, D. , “A survey on 3GPP heterogeneous networks”, Wireless Communications, IEEE, Page(s): 10-21, June 2011
〔7〕Mohammad Ahmad Joud, “Pico Cell Range Expansion toward LTE-Advanced Wireless Heterogeneous Networks,” Universitat Politècnica de Catalunya (UPC), January. 2013
〔8〕K. Dimou, W. Min, Y. Yu, M. Kazmi, A. Larmo, J. Pettersson, W. Muller, and Y. Timner,“Handover within 3GPP LTE: Design Principles and Performance,”in IEEE 70th Vehicular Technology Conference Fall (VTC 2009-Fall), Anchorage, Alaska USA, 2009, pp. 1-5
〔9〕Policy and charging control architecture, 3GPP Technical specification 23.203 version 13.9.0(Release 13), October 2016
〔10〕Kenneth Munson and Taylor John William Ransom, ”Jane′s Pocket Book of Remotely Piloted Vehicles: Robot Aircraft Today”, Collier Books, 1977
〔11〕IMT-Advanced (4G) Mobile wireless broadband on the anvil New ITU radio interface standards to revolutionize mobile communication, ITU Press Release 21, October 2009
〔12〕Maiwald, F., and Schulte, A., “Using LTE-Networks for UAS Communication”, Proceeding of 36th European Telemetry and Test Conference, May 2016.
〔13〕立石賢吾, “練好機器學習的基本功”,2018
〔14〕KEVIN, “機器學習(Machine Learning)介紹”, 2016,取自
https://reurl.cc/RZKGe
〔15〕陳鍾誠, “K-Means 分群演算法”, 2013,取自https://reurl.cc/Qv1AO
〔16〕Zhou, Y., Cheng, N., Lu, N., Shen, X.: Multi-UAV-Aided Networks Aerial–Ground Cooperative Vehicular Networking Architecture. In: IEEE Vehicular Technology Magazine,2015
〔17〕周迪之, “開源網絡模擬器NS-3架構與實踐”,2018
〔18〕Z. Li et al., “Joint Optimization on Load Balancing and Network Load in 3GPP LTE Multi-cell Networks,” IEEE Conference on WCSP, pp. 1-5, Nov. 2011
〔19〕C. T. C. N. Ganganath and C. K. Tse, “Data clustering with cluster size constraints using a modified k-means algorithm, ” in 2014 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, Oct 2014, pp. 158-161
〔20〕ETSI TR 136 931 V9.0.0 (2011-05)LTE; Evolved Universal Terrestrial Radio Access (E-UTRA);Radio Frequency (RF) requirements for LTE Pico Node B(3GPP TR 36.931 version 9.0.0 Release 9)
〔21〕I. Balan, T. Jansen, B. Sas, I. Moerman, T. Kurner, “Enhanced weighted performance based handover optimization in LTE”, Future Network and Mobile Summit 2011 Conference
〔22〕M. Song, J. Liu, S. Yang, “A Mobility Prediction and Delay Prediction Routing Protocol for UAV Networks”, Conference: 2018 10th International Conference on Wireless Communications and Signal Processing (WCSP)
〔23〕Xiao Zhang, Haijun Wang , Haitao Zhao, “An SDN framework for UAV backbone network towards knowledge centric networking”, IEEE INFOCOM 2018 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)
〔24〕D. Brockmann, L. Hufnagel, and T. Geisel, “ The scaling laws of human travel, ” Nature, pages 462-465, 2006.
〔25〕M. C. Gonzalez, C. A. Hidalgo, and A. Barabasi, “ Understanding individual human mobility patterns, ” Nature, pages 779-782, 2008.
〔26〕I. Rhee, M. Shin, S. Hong, K. Lee, and S. Chong, “ On the levy walk nature of human mobility, ” In Proceedings of INFOCOM 2008.
〔27〕T. Karagiannis, J.-Y. L. Boudec, and M. Vojnovic, “ Power law and exponential decay of inter contact times between mobile devices, ” In Proc. of MobiCom 2007.
〔28〕M. Kim, D. Kotz, and S. Kim, “ Extracting a mobility model from real user traces, ” In Proceedings of INFOCOM 2006.
〔29〕C. Song, Z. Qu, N. Blumm, and A. Barabasi, “ Limits of predictability in human mobility, ” Science, pages 1018-1021, 2010.
〔30〕J. Lyu, Y. Zeng, R. Zhang, and T. J. Lim, “Placement optimization of uav mounted mobile base stations,” IEEE Communications Letters, vol. 21, no. 3, pp. 604–607, March 2017.
〔31〕P. Yang, X. Cao, C. Yin, Z. Xiao, X. Xi, and D. Wu, “Proactive drone-cell deployment:Overload relief for a cellular network under flash crowd traffic,” IEEE Transactions on Intelligent Transportation Systems, vol. 18, no. 10, pp. 2877–2892, Oct 2017.
〔32〕S. Weisen, L. Junling, X. Wenchao, Z. Haibo, Z. Ning, and S. X, “3d drone cell deployment optimization for drone assisted radio access networks,” Proc. IEEE/CIC ICCC, pp. 1–6, 2017.
〔33〕工研院 資訊與通訊研究所,“Generate Network Topology”,2018
指導教授 吳中實 鍾耀梁(Jung-Shyr Wu Yao-Liang Chung) 審核日期 2019-7-29 推文 plurk
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