在非地面網路(Non Terrestrial Networks, NTN)使用無人機(Unmanned Aerial Vehicle, UAV)蒐集與傳送感測器(Sensor)的封包時，感測器封包標頭(Header)帶來的額外負載(Overhead)會導致頻寬(Bandwidth)產生非必要的浪費，在衛星(Satellite, SAT)傳送資料封包至地面傳收站(Ground Station, GS)時，我們必需尋找一台最佳的UAV來減少資料傳輸的延遲。為了解決這兩個問題，本論文設計一個資料合併與轉傳(Data Aggregation and Forwarding, DAF)的機制，此機制分成兩個部份，第一個部份是短封包整合(Short Packet Aggregation, SPA)的演算法，此演算法在長距離廣域網路(Long Range Wide-Area Networks, LoRaWAN)的感測器中使用UAV蒐集感測器的資料，接著UAV將資料位元組(Byte)較少的感測器封包做合併，最後UAV會將LoRaWAN的協定轉換為SAT使用的第二代數位影片廣播衛星(Digital Video Broadcasting Satellite Second Generation, DVB-S2)的協定。DAF的第二個部份是動態選擇無人機(Dynamic Unmanned Aerial Vehicle Selection, DUS)來傳送資料到GS的演算法，我們會根據接收到的經緯度與高度來選擇最佳的UAV當作路由節點，最後SAT將封包經由此UAV轉傳至GS來完成端點到端點的傳輸。為了驗證我們所提出的DAF機制在網路效能的優越性，我們使用C語言來撰寫模擬程式，此程式主要分為四個部份，第一個部份是根據感測器資料大小的比例與數量來合併感測器的資料，第二個部份是在UAV上設計一個閘道器來將不同的協定做轉換，第三個部份是使用經緯度與高度計算最佳的UAV路由，第四個部份是UAV移動位置來傳送資料。從實驗結果中，我們分析在不同感測器數量與感測器資料長度比例所節省的頻寬與延遲時間，另外我們比較DAF與廣播(Broadcast)機制所佔用的頻寬與延遲時間。

In a Non-Terrestrial Network (NTN) utilizing Unmanned Aerial Vehicles (UAV)
to collect and transmit packets from sensors, the overhead in packet headers leads to
unnecessary bandwidth wastage. When a Satellite (SAT) transmits data packets to a
Ground Station (GS), finding an optimal UAV to minimize data transmission latency is
crucial. To address these issues, in this thesis, we proposes a Data Aggregation and
Forwarding (DAF) mechanism. This mechanism consists of two modules. Short Packet
Aggregation (SPA) algorithm and Dynamic UAV Selection (DUS) algorithm. In SPA,
a UAV collects sensor data from Long Range Wide-Area Networks (LoRaWAN) and it
then aggregates sensor packets of smaller sizes. Finally, the UAV has to convert the
LoRaWAN protocol to the Digital Video Broadcasting Satellite 2nd Generation (DVB
S2) protocol. In DUS, to minimize the end-to-end transmission delay, transmitting data
to a GS is based on the most adequate latitude, longitude, and altitude of a UAV acting
as a routing relay. To validate our proposed DAF mechanism, we perform a simulation
written by C language. The simulation program consists of four parts. The first part
aggregates short-size packets based on a ratio of different data sizes. The second part is
a gateway on the UAV for protocol conversions. The third part uses latitude, longitude,
and altitude to calculate the optimal route via a UAV. The last part simulates a moving
UAV while relaying the packet transmission. From the experimental results, we analyze
the bandwidth and latency savings under different sensor quantities and different ratios
of packet sizes. Furthermore, we compare the bandwidth and latency between the
proposed DAF and a broadcasting scheme.

論文審定書..................................................................................................................... i
摘要................................................................................................................................ ii
Abstract ......................................................................................................................... iii
目錄............................................................................................................................... iv
圖目錄........................................................................................................................... vi
表目錄......................................................................................................................... viii
第一章 導論.................................................................................................................. 1
1.1 研究動機......................................................................................................... 1
1.2 研究方法......................................................................................................... 1
1.3 章節介紹......................................................................................................... 2
第二章 無人機的封包合併與轉傳.............................................................................. 3
2.1 LoRaWAN的資料蒐集................................................................................... 3
2.1.1 蒐集資料的網路拓樸.......................................................................... 3
2.1.2 LoRaWAN............................................................................................. 5
2.1.3資料合併............................................................................................... 9
2.2 非地面網路的資料轉傳............................................................................... 10
2.2.1 衛星與無人機的轉傳........................................................................ 10
2.2.2 無人機的經緯度與距離.................................................................... 12
2.3 相關研究....................................................................................................... 13
第三章 非地面網路的資料合併與轉傳.................................................................... 17
3.1 感測器封包的傳輸....................................................................................... 17
3.2 無人機的封包整合....................................................................................... 18
3.2.1 短封包的整合.................................................................................... 18
3.2.2 短封包整合的流程............................................................................ 20
3.2.3 合併封包的拆解流程........................................................................ 22
3.3 衛星與無人機間的傳輸路徑....................................................................... 23
3.3.1 動態選擇無人機的格式.................................................................... 23
3.3.2 無人機的尋找.................................................................................... 24
3.3.3 無人機尋找的流程............................................................................ 26
3.4 LoRa與DVB-S2的協定轉換 ...................................................................... 28
第四章 模擬與結果分析............................................................................................ 32
4.1 模擬拓樸....................................................................................................... 32
4.2 模擬程式的虛擬碼....................................................................................... 33
4.2.1 感測器的虛擬碼................................................................................ 33
4.2.2資料合併與協定轉換的虛擬碼......................................................... 36
4.2.2 衛星尋找無人機的虛擬碼................................................................ 43
4.3模擬結果與分析............................................................................................ 54
4.3.1資料合併的無人機............................................................................. 55
4.3.2動態選擇無人機路由......................................................................... 59
4.3.3資料合併與路由尋找......................................................................... 61
第五章 結論與未來工作............................................................................................ 67
5.1 結論............................................................................................................... 67
5.2 模擬程式所花的時間................................................................................... 68
5.3 未來工作....................................................................................................... 68
Reference ..................................................................................................................... 69
Acronyms ..................................................................................................................... 74
Index ............................................................................................................................ 78

[1] 3GPP, “Study on New Radio (NR) to Support Non-Terrestrial Networks,” 3GPP
TR 38.811, Ver. 15.4.0, Release 15, Sep. 2020.
[2] S. Zhang, “Research on Emergency Coverage Capability of Fixed-Wing UAV
Based on 5G,” 2020 International Wireless Communications and Mobile
Computing, pp. 680-684, Jun. 2020.
[3] C. Zhan and H. Lai, “Energy Minimization in Internet-of-Things System Based on
Rotary-Wing UAV,” IEEE Wireless Communications Letters, vol. 8, pp. 1341-1344,
Oct. 2019.
[4] Y. Hmamouche, M. Benjillali, and S. Saoudi, “Terrestrial Connectivity Through
Constellations of High Altitude Platform Station (HAPS),” 2022 11th International
Symposium on Signal Image Video and Communications, pp. 1-6, May 2022.
[5] P. He, J. Hu, X. Fan, D. Wu, R. Wang, and Y. Cui, “Load-Balanced Collaborative
Offloading for LEO Satellite Networks,” IEEE Internet of Things Journal, vol. 10,
pp. 19075-19086, Nov. 2023.
[6] LoRa Alliance Technical Committee, “LoRaWAN™ 1.0.3 Specification,” LoRa
Alliance Technical Committee, Ver. 1.0.3, Jul. 2018.
[7] SEMTECH, “SX1272/3/6/7/8: LoRa Modem,” SEMTECH, Ver. AN1200.13, July.
2018.
[8] SEMTECH, “LoRa™
Modulation Basics,” SEMTECH, Ver. AN1200.22,
May 2015.
[9] R. Braden, “Requirements for Internet Hosts - Communication Layers,” RFC 1122,
Oct. 1989.
[10] ETSI, “Frame Structure Channel Coding and Modulation for a Second Generation
Digital Transmission System for Cable Systems (DVB-C2),” ETSI EN 302 769, Ver.
1.2.1, Dec. 2010.
[11] ETSI, “Generic Stream Encapsulation (GSE); Part 1: Protocol,” ETSI TS 102 606
1, Ver. 1.2.1, Jun. 2014.
[12] ETSI, “Second Generation DVB Interactive Satellite System (DVB-RCS2); Part
2: Lower Layers for Satellite Standard,” ETSI EN 301 545-2, Ver. 1.4.1, Jan. 2024.
[13] T. Coloşi, M. Ungureşan, and V. Mureşan, “Numerical Simulation of Distributed
Parameter Processes Using Cartesian Spherical Cylindrical and Spiral Coordinates,”
2014 IEEE International Conference on Automation, pp. 1-6, May 2014.
[14] Y. Zhang, H. Dong, and F. Song, “Design and Realization of an UAV 3D Track
Accuracy Evaluation and Detection Device,” 2021 4th International Conference on
Intelligent Robotics and Control Engineering, pp. 51-56, Sep. 2018.
[15] P. Markstein, “A Fast-Start Method for Computing the Inverse Tangent,” 17th
IEEE Symposium on Computer Arithmetic, pp. 266-271, Jun. 2005.
[16] A. Andreou, X. Zhu, Y. Jiang, J. Cao, X. Xiong, and H. Wang, “Status Prediction
and Data Aggregation for AoI-Oriented Short-Packet Transmission in Industrial
IoT,” IEEE Transacovertions on Vehicular Technology, vol. 72, pp. 9757-9769,
Aug. 2023.
[17] L. Bai, J. Lin, J. Wang, R. Han, and J. Choi, “Data Aggregation in UAV-Aided
Random Access for Internet of Vehicles,” IEEE Internet of Things Journal, vol. 9,
pp. 5755-5764, Apr. 2022.
[18] Z. Yang, H. Liu, Y. Chen, X. Zhu, Y. Ning, and W. Zhu, “UEE-RPL: a UAV
Based Energy Efficient Routing for Internet of Things,” IEEE Transactions on
Green Communications and Networking, vol. 5, pp. 1333-1344, Sep. 2021.
[19] M. Kang and S. W. Jeon, “Energy-Efficient Data Aggregation and Collection for
Multi-UAV-Enabled IoT Networks,” IEEE Wireless Communications Letters, vol.
13, pp. 1004-1008, Apr. 2024.
[20] O. Ghdiri, W. Jaafar, S. Alfattani, J. B. Abderrazak, and H. Yanikomeroglu,
“Energy-Efficient Multi-UAV Data Collection for IoT Networks with Time
Deadlines,” GLOBECOM 2020 - 2020 IEEE Global Communications Conference,
pp. 1-6, Dec. 2020.
[21] M. T. Nguyen, T. T. Bui, L. D. Nguyen, E. G. Palacios, H. J. Zepernick, H. Shin,
and T. Q. Duong, “Real-Time Optimized Clustering and Caching for 6G Satellite
UAV-Terrestrial Networks,” IEEE Transactions on Intelligent Transportation
Systems, vol. 25, pp. 3009-3019, Mar. 2024.
[22] T. Salam, W. U. Rehman, and X. Tao, “Data Aggregation in Massive Machine
Type Communication: Challenges and Solutions,” IEEE Access, vol. 7, pp. 41921
41946, Apr. 2019.
[23] D. Wang, A. Traspadini, M. Giordani, M. S. Alouini, and M. Zorzi, “On the
Performance of Non-Terrestrial Networks to Support the Internet of Things,” 2022
56th Asilomar Conference on Signals, Systems, and Computers, pp. 881-887, Nov.
2022.
[24] X. Wei, H. Yang, and W. Huang, “Low-Delay Routing Scheme for UAV
Communications in Smart Cities,” IEEE Internet of Things Journal, vol. 10, pp.
18837-18843, Nov. 2023.
[25] C. Zhou, C. Dong, X. Zhu, and L. Zhang, “Multi-Antenna Based Fast Routing
Recovery Protocol for Dynamic UAV Networks,” 2022 IEEE Intl Conf on Parallel
& Distributed Processing with Applications, Big Data & Cloud Computing,
Sustainable Computing & Communications, Social Computing & Networking, pp.
507-514, Dec. 2022.
[26] K. He, Q. Zhou, Y. Shen, J. Gao, and Z. Shuai, “Spatiotemporal Precise Routing
Strategy for Multi-UAV-Based Power Line Inspection Using Hybrid Network of
FANET and Satellite Internet,” 2023 IEEE/IAS Industrial and Commercial Power
System Asia, pp. 1013-1018, Jul. 2023.
[27] K. N. Praveen, K. M. Sivarama, and M. B. Naveen, “Performance Analysis of a
UAV-Based Non-Terrestrial Network (NTN) Using NB-IoT,” 2023 IEEE Wireless
Communications and Networking Conference, pp. 1-6, Mar. 2023.
[28] Z. Jia, M. Sheng, J. Li, D. Niyato, and Z. Han, “LEO-Satellite-Assisted UAV:
Joint Trajectory and Data Collection for Internet of Remote Things in 6G Aerial
Access Networks,” IEEE Internet of Things Journal, vol. 8, pp. 9814-9826, Jun.
2021.
[29] H. K. Alkahtani, H. Mahgoub, F. A. Alotaibi, K. M. Othman, R. Allafi, and A. S.
Salama, “Design of Hybrid Snake Optimizer Based Route Selection Approach for
Unmanned Aerial Vehicles Communication,” IEEE Access, vol. 12, pp. 54426
54434, Mar. 2024.
[30] L. Xu, K. Adebo, J. Zhao, and L. Miao, “Distributed Drones for Power Line
Inspection with Weighted Consensus Control in Dynamic Network Systems,” 2019
IEEE 3rd International Electrical and Energy Conference, pp. 2049-2054, Sep.
2019.