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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 謝宏昀 | zh_TW |
| dc.contributor.advisor | Hung-Yun Hsieh | en |
| dc.contributor.author | 閻帛佑 | zh_TW |
| dc.contributor.author | Po-Yu Yen | en |
| dc.date.accessioned | 2026-03-10T16:06:28Z | - |
| dc.date.available | 2026-03-11 | - |
| dc.date.copyright | 2026-03-10 | - |
| dc.date.issued | 2026 | - |
| dc.date.submitted | 2026-02-25 | - |
| dc.identifier.citation | [1] 3GPP, “3GPP TS 38.213 v18.3.0 (Release 18): NR; physical layer procedures for control,” 3rd Generation Partnership Project (3GPP), Tech. Rep., Sep 2025. Online Available at: https://www.3gpp.org/dynareport/38213.htm
[2] D.-H. Jung, J.-G. Ryu, W.-J. Byun, and J. Choi, “Performance analysis of satellite communication system under the shadowed-rician fading: A stochastic geometry approach,” IEEE Transactions on Communications, vol. 70, no. 4, pp. 2707–2721, 2022. [3] M. N. Ahangar, Q. Z. Ahmed, M. Hafeez, and M. S. Bashir, “Artificial intelligence-aided beam tracking in autonomous vehicles: State of the art and future directions,” IEEE Transactions on Intelligent Transportation Systems, vol. 26, no. 11, pp. 18 385–18 403, 2025. [4] X. Li, L. Zhang, L. Jiang, and X.-G. Xia, “Initial beam association schemes for mmwave cellular networks under blockage,” IEEE Transactions on Vehicular Technology, 2018. [5] Z. Lin, Z. Ni, L. Kuang, C. Jiang, and Z. Huang, “Satellite-terrestrial coordinated multi-satellite beam hopping scheduling based on multi-agent deep reinforcement learning,” IEEE Transactions on Wireless Communications, vol. 23, no. 8, pp. 10 091–10 103, 2024. [6] W. Wang, T. Chen, R. Ding, G. Seco-Granados, L. You, and X. Gao, “Location-based timing advance estimation for 5g integrated leo satellite communications,” IEEE Transactions on Vehicular Technology, vol. 70, no. 6, pp.6002–6017, 2021. [7] L. Chen, L. Wu, E. Lagunas, A. Wang, L. Lei, S. Chatzinotas, and B. Ottersten, “Joint power allocation and beam scheduling in beam-hopping satellites: A two-stage framework with a probabilistic perspective,” IEEE Transactions on Wireless Communications, vol. 23, no. 10, pp. 14 685–14 701, 2024. [8] S. Guo, L. Zhao, and Y. Cui, “Latency optimization of LEO satellite communication systems with beam hopping,” in 2022 IEEE International Conferenceon Satellite Computing (Satellite), 2022, pp. 37–42. [9] C.-W. Weng, B. P. S. Sahoo, H.-Y. Wei, and C.-H. Yu, “Directional reference signal design for 5G millimeter wave cellular systems,” IEEE Transactions on Vehicular Technology, vol. 67, no. 11, pp. 10 740–10 751, 2018. [10] 3GPP, “Study on New Radio (NR) to support non-terrestrial networks,”3rd Generation Partnership Project (3GPP), Technical Report TR 38.811, June 2020, version 15.4.0. Online Available at: https://www.3gpp.org/ftp/Specs/archive/38 series/38.811/ [11] “Solutions for nr to support non-terrestrial networks (NTN),” 3rd Generation Partnership Project (3GPP), Technical Report TR 38.821, 2023, release 16. Online Available at: https://www.3gpp.org/dynareport/38821.htm [12] Y. Su, Y. Liu, Y. Zhou, J. Yuan, H. Cao, and J. Shi, “Broadband LEO satellite communications: Architectures and key technologies,” IEEE Wireless Communications, vol. 26, no. 2, pp. 55–61, 2019. [13] 3rd Generation Partnership Project (3GPP), “Study on using satellite access in 5G,” 3GPP, TR 22.822, June 2018, release 16. Online Available at: https://www.3gpp.org/DynaReport/22822.htm [14] “3GPP TS 38.211 V18.2.0 (Release 18): NR; physical channels and modulation,” 3GPP, Tech. Rep., Sep 2025. Online Available at: https://www.3gpp.org/dynareport/38211.htm [15] 3GPP, “Radio Resource Control (RRC) protocol specification,” 3rd Generation Partnership Project (3GPP), Technical Report TR 38.331, March 2024, version 18.1.0. Online Available at: https://www.3gpp.org/ftp/Specs/archive/38 series/38.331/ [16] “NR; NR and NG-RAN overall description; stage-2,” 3rd Generation Partnership Project (3GPP), Technical Specification TS 38.300, 2024, release 18. Online Available at: https://www.3gpp.org/dynareport/38300.htm [17] R. P. Brent, Algorithms for Minimization Without Derivatives. Cliffs, NJ: Prentice-Hall, 1973. Englewood [18] S. Boyd and L. Vandenberghe, Convex Optimization. Press, 2004. Cambridge University [19] J. Nocedal and S. J. Wright, Numerical Optimization, 2nd ed. Springer, 2006. [20] Z. Weng, Z. Xiao, M. Zhang, M. Yi, and L. Jiang, “Beam management in millimeter-wave communications for 5g and beyond: A survey,” IEEE Access, vol. 8, pp. 132 908–132 930, 2020. [21] A. Garc´ıa-Rodr´ıguez, M. Cierny, M. H. Dahri, and P. Kela, “Machine-learning-aided method for optimizing beam selection and update time in 5g nr,” Scientific Reports, vol. 14, no. 1, p. 19055, 2024. [22] M. G. Kibria, E. Lagunas, N. Maturo, D. Spano, and S. Chatzinotas, “Precoded cluster hopping in multi-beam high throughput satellite systems,” in 2019 IEEE Global Communications Conference (GLOBECOM), 2019, pp. 1–6. [23] 3GPP RAN4, “Topic summary for [114][230] NR NTN ph3 part2,” 3GPP TSG RAN WG4, Tech. Rep. R4-2500544, January 2025, rAN4#114 (electronic meeting). Online Available at: https://www.3gpp.org/ftp/tsg ran/WG4 Radio/TSGR4 114/Inbox/Drafts/ [24] 3GPP RAN1, “Feature lead summary #1 for NR NTN phase 3 (nr-ntn-ph3),” 2024, rAN1#116 Inbox Draft: R1-24xxxxx. Online Available at: https://www.3gpp.org/ftp/tsg ran/WG1 RL1/TSGR1 116/Inbox/drafts/ [25] A. Kumar Meshram, S. Kumar, J. Querol, S. Andrenacci, and S. Chatzinotas, “Reduced complexity initial synchronization for 5g nr multibeam leo-based non-terrestrial networks,” IEEE Open Journal of the Communications Society, vol. 6, pp. 1528–1551, 2025. [26] J. Wang, C. Jiang, L. Kuang, and R. Han, “Satellite multi-beam collaborative scheduling in satellite aviation communications,” IEEE Transactions on Wireless Communications, vol. 23, no. 3, pp. 2097–2111, 2024. [27] Y. Li, J. G. Andrews, F. Baccelli, T. D. Novlan, and C. J. Zhang, “Design and analysis of initial access in millimeter wave cellular networks,” IEEE Transactions on Wireless Communications, vol. 16, no. 10, pp. 6409–6425,2017. | - |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/102031 | - |
| dc.description.abstract | 在低軌道（LEO）衛星通訊系統中，同步訊號搜索延遲（cell search delay） 是一項關鍵的效能指標，其表現受同步訊號區塊（SSB）傳輸功率與週期性顯著影響。較高的傳輸功率可提升偵測成功率，而較短的週期有助於縮短等待時間，兩者皆能有效降低小區搜尋遲。然而，這兩種手段都會增加衛星有限的電力負擔，因此必須在功率與週期性之間進行權衡。此外，現行 3GPP的SSB聯組（burst）設計主要針對地面行動網路，對於高度動態的 LEO 衛星環境並不適用。為克服此限制，本論文突破傳統的 SSB突發框架，提出一個聯合SSB功率與週期性最佳化架構，以最小化使用者設備（UE）的小區搜尋延遲。針對此非凸問題，我們首先利用黃金比例搜尋（golden-section search）建立資料驅動的均勻初始化，以確保演算法的穩定收斂；隨後提出一種交替最佳化演算法，將原問題分解為凸性的週期性子問題與基於序列二次規劃（SQP）的功率子問題。在36個六邊形小區覆蓋的 LEO衛星足跡下，針對不同遮蔽萊斯衰落（shadowed-Rician）通道條件進行模擬，結果顯示本方法具有顯著優勢。與均勻功率與週期性配置相比，平均延遲降低 48.9%；相較僅進行功率最佳化與僅進行週期性最佳化，分別提升 15.1%與29.3%；與5G SSB聯組基準（2、4、8聯組配置）相比，則實現 18.6–47.6%的效能增益。這些結果證明了基於 LEO波束跳頻特性的自適應小區層級 SSB資源配置策略的有效性，成功填補了現有研究中的關鍵空白。 | zh_TW |
| dc.description.abstract | Cell search delay, a critical performance metric in Low Earth Orbit (LEO) satellite communication systems, is significantly impacted by Synchronization Signal Block (SSB) transmit power and periodicity. Higher transmit power improves detection success rates while shorter periodicity reduces waiting time, both helping to reduce cell search delay. However, both approaches strain the limited onboard power budget, necessitating careful tradeoffs between power and periodicity. Moreover, current 3GPP SSB burst designs are primarily suited for terrestrial networks and prove inadequate for LEO satellite networks with their highly dynamic environments. Therefore, this thesis breaks from the conventional SSB burst framework and proposes a joint SSB power and periodicity optimization framework to minimize UE cell search delay. To solve this non-convex problem, we first determine a data-driven uniform initialization via golden-section search to ensure robust convergence. Then, a novel alternating optimization algorithm decomposes the original problem into convex periodicity subproblems and sequential quadratic programming (SQP)-based power subproblems. Extensive simulations over 36 hexagonal-cell LEO footprints with varying shadowed-Rician channel severities demonstrate superior performance. The proposed method yields a 48.9% average delay reduction compared to uniform power and periodicity allocation, a 15.1% improvement over power-only optimization, a 29.3% improvement over periodicity-only optimization, and 18.6–47.6% gains against 5G SSB burst baselines with 2, 4, and 8 bursts. These results highlight the efficacy of adaptive cell-level SSB resource allocation tailored to LEO beam-hopping dynamics, addressing a critical gap in prior research. | en |
| dc.description.provenance | Submitted by admin ntu (admin@lib.ntu.edu.tw) on 2026-03-10T16:06:28Z No. of bitstreams: 0 | en |
| dc.description.provenance | Made available in DSpace on 2026-03-10T16:06:28Z (GMT). No. of bitstreams: 0 | en |
| dc.description.tableofcontents | 口試委員審定書. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ii
致謝. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii 中文摘要. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iv ABSTRACT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v TABLEOFCONTENTS . . . . . . . . . . . . . . . . . . . . . . . . . vi LISTOFTABLES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix LISTOFFIGURES . . . . . . . . . . . . . . . . . . . . . . . . . . . . x CHAPTER1 INTRODUCTION . . . . . . . . . . . . . . . . . . . 1 CHAPTER2 BACKGROUND AND RELATED WORK. . . . 6 2.1 Non-Terrestrial Networks . . . . . . . . . . . . . . . . . . . . . . . 6 2.2 Initial Access Procedure . . . . . . . . . . . . . . . . . . . . . . . . 8 2.2.1 Synchronization Signal Block . . . . . . . . . . . . . . . . . 8 2.2.2 Random Access Procedure . . . . . . . . . . . . . . . . . . 10 2.3 Beam Adjustment in LEO Satellite Network . . . . . . . . . . . . 12 2.3.1 Beam Hopping . . . . . . . . . . . . . . . . . . . . . . . . . 12 2.3.2 Quasi-Earth-Fixed Cell and Satellite Switch with Resynchronization . . . . . . . . . . . . . . . . . . . . . . . . . . 12 2.4 Optimization Methods . . . . . . . . . . . . . . . . . . . . . . . . 13 2.4.1 Golden-Section Search . . . . . . . . . . . . . . . . . . . . . 13 2.4.2 Convex Optimization . . . . . . . . . . . . . . . . . . . . . 15 2.4.3 Sequential Quadratic Programming . . . . . . . . . . . . . 16 2.5 Related Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 2.5.1 Cell Search in Terrestrial Networks . . . . . . . . . . . . . . 18 2.5.2 Resource allocation in LEO Satellite Systems . . . . . . . . 18 2.5.3 SSB Utilization in LEO Satellite Systems . . . . . . . . . . 19 2.5.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 CHAPTER 3 SYSTEM MODEL. . . . . . . . . . . . . . . . . . . . 21 3.1 System Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 3.2 Channel Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 3.2.1 Free Space Path Loss . . . . . . . . . . . . . . . . . . . . . 21 3.2.2 Shadowed-Rician Fading Channel . . . . . . . . . . . . . . 22 3.3 Joint Power-Periodicity Optimization on SSB . . . . . . . . . . . . 23 3.3.1 Synchronization Signal Block Periodicity Model . . . . . . 23 3.3.2 Transmit Power Model . . . . . . . . . . . . . . . . . . . . 24 3.4 UE Cell Search Delay . . . . . . . . . . . . . . . . . . . . . . . . . 25 3.5 Problem Formulation . . . . . . . . . . . . . . . . . . . . . . . . . 26 CHAPTER 4 PROPOSED ALGORITHM. . . . . . . . . . . . . . 29 4.1 Expectation Derivation of Cell Search Delay . . . . . . . . . . . . 30 4.1.1 Expectation of Initial Waiting Time E[βk] . . . . . . . . . . 30 4.1.2 Expectation of Retry Delay E[γk] . . . . . . . . . . . . . . 30 4.1.3 Expectation of Cell Search Delay E[αk] . . . . . . . . . . . 30 4.2 Initialization Strategy . . . . . . . . . . . . . . . . . . . . . . . . . 31 4.3 Alternating Optimization Framework . . . . . . . . . . . . . . . . 33 4.3.1 Periodicity Subproblem . . . . . . . . . . . . . . . . . . . . 33 4.3.2 Power Subproblem . . . . . . . . . . . . . . . . . . . . . . . 34 4.4 Summary of the Proposed Method . . . . . . . . . . . . . . . . . . 34 CHAPTER 5 PERFORMANCE EVALUATION. . . . . . . . . . 36 5.1 Simulation Setup . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 5.1.1 System Configuration . . . . . . . . . . . . . . . . . . . . . 36 5.1.2 Channel Model and Parameter Settings . . . . . . . . . . . 38 5.2 Channel Quality and Resource Allocation Analysis . . . . . . . . . 40 5.2.1 Average Power and Periodicity Analysis in Uniform Chan-nel Quality Scenario . . . . . . . . . . . . . . . . . . . . . . 40 5.2.2 Power and Periodicity Allocation in Diverse Channel Qual-ity across Cells . . . . . . . . . . . . . . . . . . . . . . . . . 42 5.3 Component-wise Analysis in Realistic Scenarios . . . . . . . . . . . 43 5.3.1 Relationship between Number of UE and Periodicity . . . . 44 5.3.2 Relationship between Channel Model and Power Allocation 45 5.3.3 Relationship between Power Allocation and SSB Periodicity 46 5.3.4 Initialization Parameter r Evaluation . . . . . . . . . . . . 47 5.3.5 Convergence Analysis . . . . . . . . . . . . . . . . . . . . . 48 5.4 Performance Comparison under Different Methods . . . . . . . . . 48 5.4.1 Delay Comparison across Different Optimization Variables . 51 5.4.2 Delay Comparison across Different SSB Burst Numbers . . 54 5.5 Sensitivity Analysis of System Parameters . . . . . . . . . . . . . . 58 5.5.1 Impact of Satellite Position on Cell Search Delay . . . . . . 58 5.5.2 Impact of Number of UEs on Cell Search Delay . . . . . . . 59 CHAPTER 6 CONCLUSION AND FUTURE WORK. . . . . . 61 6.1 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61 6.2 Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61 REFERENCES. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63 | - |
| dc.language.iso | en | - |
| dc.subject | 低軌道衛星通訊 | - |
| dc.subject | 同步訊號搜索延遲 | - |
| dc.subject | 同步訊號區塊功率 | - |
| dc.subject | 同步訊號區塊週期 | - |
| dc.subject | 非凸函數最佳化 | - |
| dc.subject | Low Earth Orbit Satellite Communication | - |
| dc.subject | Cell Search Delay | - |
| dc.subject | SSB Power | - |
| dc.subject | SSB Periodicity | - |
| dc.subject | Non Convex Optimization | - |
| dc.title | 縮短低軌衛星通訊初始同步訊號搜索延遲之聯合功率與週期最佳化設計 | zh_TW |
| dc.title | Minimizing Cell Search Delay through Power and Periodicity Optimization of Synchronization Signal Blocks in Low Earth Orbit Satellite Communications | en |
| dc.type | Thesis | - |
| dc.date.schoolyear | 114-1 | - |
| dc.description.degree | 碩士 | - |
| dc.contributor.oralexamcommittee | 蘇炫榮;黃楚翔;李佳翰 | zh_TW |
| dc.contributor.oralexamcommittee | Hsuan-Jung Su;Chu-Hsiang Huang;Chia-Han Lee | en |
| dc.subject.keyword | 低軌道衛星通訊,同步訊號搜索延遲同步訊號區塊功率同步訊號區塊週期非凸函數最佳化 | zh_TW |
| dc.subject.keyword | Low Earth Orbit Satellite Communication,Cell Search DelaySSB PowerSSB PeriodicityNon Convex Optimization | en |
| dc.relation.page | 65 | - |
| dc.identifier.doi | 10.6342/NTU202600798 | - |
| dc.rights.note | 同意授權(全球公開) | - |
| dc.date.accepted | 2026-02-25 | - |
| dc.contributor.author-college | 電機資訊學院 | - |
| dc.contributor.author-dept | 電信工程學研究所 | - |
| dc.date.embargo-lift | 2031-02-24 | - |
| 顯示於系所單位： | 電信工程學研究所 | |
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