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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/98623完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 魏宏宇 | zh_TW |
| dc.contributor.advisor | Hung-Yu Wei | en |
| dc.contributor.author | 丁柏豪 | zh_TW |
| dc.contributor.author | Po-Hao Ting | en |
| dc.date.accessioned | 2025-08-18T01:07:13Z | - |
| dc.date.available | 2025-08-18 | - |
| dc.date.copyright | 2025-08-15 | - |
| dc.date.issued | 2025 | - |
| dc.date.submitted | 2025-08-05 | - |
| dc.identifier.citation | [1] IEEE Standards Association, “IEEE Standard for Information Technology –Telecommunications and Information Exchange between Systems – Local and Metropolitan Area Networks – Specific Requirements – Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications – Amendment 1: Enhancements for High-Efficiency WLAN,” IEEE Std 802.11ax-2021 (Amendment to IEEE Std 802.11-2020), pp. 1–767, 2021.
[2] W. Qiu, G. Chen, K. N. Nguyen, A. Sehgal, P. Nayak, and J. Choi, “Category-Based 802.11ax Target Wake Time Solution,” IEEE Access, vol. 9, pp. 100 154–100 172, 2021. [3] C. Puligheddu, F. Busacca, R. Rusca, F. Raviglione, C. Casetti, C. F. Chiasserini, and S. Palazzo, “Target Wake Time Scheduling for Time-Sensitive Networking in the Industrial IoT,” in 2024 IEEE 35th International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), 2024, pp. 1–7. [4] X. Peng, Y. Fang, C. Li, and L. Guo, “Access Point Coordination Based TWT Scheduling for the Next Generation WLAN,” in 2024 13th International Conference on Communications, Circuits and Systems (ICCCAS), 2024, pp. 238–243. [5] X. Jin, Y. Long, X. Fang, R. He, and H. Ju, “Energy Consumption Optimization under Multi-link Target Wake Time scheme in WLANs,” in 2022 IEEE/CIC International Conference on Communications in China (ICCC), 2022, pp. 1119–1124. [6] Q. Chen, “An Energy-Efficient Channel Access With Target Wake Time Scheduling for Overlapping 802.11ax Basic Service Sets,” IEEE Internet of Things Journal, vol. 9, no. 19, pp. 18 973–18 986, Oct. 2022. [7] Q. Chen, Z. Weng, X. Xu, and G. Chen, “A Target Wake Time Scheduling Scheme for Uplink Multiuser Transmission in IEEE 802.11ax-Based Next Generation WLANs,” IEEE Access, vol. 7, pp. 158 207–158 222, 2019. [8] Q. Chen and Y.-H. Zhu, “Scheduling Channel Access Based on Target Wake Time Mechanism in 802.11ax WLANs,” IEEE Transactions on Wireless Communications, vol. 20, no. 3, pp. 1529–1543, March 2021. [9] R. Roy, R. V. Bhat, P. Hathi, N. Akhtar, and N. M. Balasubramanya, “Maximization of Timely Throughput with Target Wake Time in IEEE 802.11ax,” in ICC 2023 - IEEE International Conference on Communications, 2023, pp. 647–652. [10] J. Sheth, V. K. Ramanna, and B. Dezfouli, “Traffic Characterization for Efficient TWT Scheduling in 802.11ax IoT Networks,” in 2023 IEEE Wireless Communications and Networking Conference (WCNC), 2023, pp. 1–6. [11] B. Schneider, R. C. Sofia, and M. Kovatsch, “A Proposal for Time-Aware Scheduling in Wireless Industrial IoT Environments,” in NOMS 2022-2022 IEEE/IFIP Network Operations and Management Symposium, 2022, pp. 1–6. [12] S. Santi, L. Tian, and J. Famaey, “Evaluation of the co-existence of RAW and TWT stations in IEEE 802.11ah using ns-3,” in 2019 Workshop on Next-Generation Wireless with ns-3 (WNGW 2019), 2019, pp. 9–12. [13] S. K. Venkateswaran, C.-L. Tai, and R. Sivakumar, “Poster: Accordion: Toward a Limited Contention Protocol for Wi-Fi 6 Scheduling,” in 24th Int. Symp. Theory, Algorithmic Foundations, Protocol Design for Mobile Networks Mobile Computing (MobiHoc ’23), 2023, pp. 1–2. [14] E. Stepanova, D. Bankov, E. Khorov, and A. Lyakhov, “On the Joint Usage of Target Wake Time and 802.11ba Wake-Up Radio,” IEEE Access, vol. 8, pp. 221 061–221 076, 2020. [15] D. Bankov, E. Khorov, A. Lyakhov, and E. Stepanova, “Clock Drift Impact on Target Wake Time in IEEE 802.11ax/ah Networks,” in 2018 Engineering and Telecommunication (EnT-MIPT), 2018, pp. 30–34. [16] M. Nurchis and B. Bellalta, “Target Wake Time: Scheduled Access in IEEE 802.11ax WLANs,” IEEE Wireless Communications, vol. 26, no. 2, pp. 142–150, April 2019. [17] J. Haxhibeqiri, X. Jiao, X. Shen, C. Pan, X. Jiang, J. Hoebeke, and I. Moerman, “Coordinated SR and Restricted TWT for Time Sensitive Applications in WiFi 7 Networks,” IEEE Communications Magazine, vol. 62, no. 8, pp. 118–124, August 2024. [18] A. Belogaev, X. Shen, C. Pan, X. Jiang, C. Blondia, and J. Famaey, “Dedicated Restricted Target Wake Time for Real-Time Applications in Wi-Fi 7,” arXiv, Feb. 2024. [19] C. Zhao, B. Li, S. Wang, and T. He, “The First Measurement Study of Target Wake Time Mechanism in 802.11ax on COTS Devices,” in ICC 2023 - IEEE International Conference on Communications, 2023, pp. 4695–4700. [20] G. Rajendran, R. Roy, P. Hathi, N. Akhtar, and S. Agnihotri, “Performance Evaluation of Video Streaming Applications with Target Wake Time in Wi-Fi 6,” in 2023 15th International Conference on COMmunication Systems & NETworkS (COM-SNETS), 2023, pp. 802–807. [21] J. Bai, H. Fang, J. Suh, O. Aboul-Magd, E. Au, and X. Wang, “Adaptive Uplink OFDMA Random Access Grouping Scheme for Ultra-Dense Networks in IEEE 802.11ax,” in 2018 IEEE/CIC International Conference on Communications in China (ICCC), 2018, pp. 34–39. [22] C. Li, Y. Fang, X. Peng, and L. Guo, “Wireless Local Area Network Service Quality Assurance Protocol Based on Cross-Cell Target Wake-up Time,” in 2024 13th International Conference on Communications, Circuits and Systems (ICCCAS), 2024, pp. 345–350. [23] J. Choi, J. Yoo, and C.-K. Kim, “A Distributed Fair Scheduling Scheme With a New Analysis Model in IEEE 802.11 Wireless LANs,” IEEE Transactions on Vehicular Technology, vol. 57, no. 5, pp. 3083–3093, Sep. 2008. [24] Y. Zheng, K. Lu, D. Wu, and Y. Fang, “Performance Analysis of IEEE 802.11 DCF in Imperfect Channels,” IEEE Transactions on Vehicular Technology, vol. 55, no. 5, pp. 1648–1656, Sep. 2006. [25] S. K. Venkateswaran, C.-L. Tai, R. Garnayak, Y. Ben-Yehzkel, Y. Alpert, and R. Sivakumar, “IEEE 802.11ax Target Wake Time: Design and Performance Analysis in ns-3,” in WNS3 ’24: Proceedings of the 2024 Workshop on ns-3, 2024, pp. 10–18. [26] E. Mozaffariar, M. Menth, and S. Avallone, “Implementation and Evaluation of IEEE 802.11ax Target Wake Time Feature in ns-3,” in WNS3 ’24: Proceedings of the 2024 Workshop on ns-3, 2024, pp. 1–9. [27] Z. Fang, J. Wang, C. Jiang, X. Wang, and Y. Ren, “Average Peak Age of Information in Underwater Information Collection With Sleep-Scheduling,” IEEE Transactions on Vehicular Technology, vol. 71, no. 9, pp. 10 132–10 136, 2022. [28] H. Pan, T.-T. Chan, J. Li, and V. C. M. Leung, “Age of information with collision-resolution random access,” IEEE Transactions on Vehicular Technology, vol. 71, no. 10, pp. 11 295–11 300, 2022. [29] S. Das and G. Ghatak, “Analysis of Age-Energy Trade-off in IoT Networks Using Stochastic Geometry,” IEEE Transactions on Green Communications and Networking, 2025. [30] F. Zhao, X. Sun, W. Zhan, X. Wang, J. Gong, and X. Chen, “Age-Energy Tradeoff in Random-Access Poisson Networks,” IEEE Transactions on Green Communications and Networking, vol. 6, no. 4, pp. 2055–2072, December 2022. [31] Q. Wang, X. Liang, H. Zhang, and L. Ge, “AoI-Aware Energy Efficiency Resource Allocation for Integrated Satellite-Terrestrial IoT Networks,” IEEE Transactions on Green Communications and Networking, vol. 9, no. 1, pp. 125–139, March 2025. [32] H.-C. Lin, K.-H. Lin, and H.-Y. Wei, “Age of Information for Power-Saving Devices with DRX Mechanism,” in ICC 2023 - IEEE International Conference on Communications, 2023, pp. 3234–3239. [33] H.-C. Lin, K.-H. Lin, and H.-Y. Wei, “Adaptive Age of Information Optimization in Rateless Coding-Based Multicast-Enabled Sensor Networks,” IEEE Journal of Selected Areas in Sensors, vol. 1, pp. 73–92, 2024. [34] S. Kaul, R. Yates, and M. Gruteser, “Real-time Status: How Often Should One Update?” in 2012 Proceedings IEEE INFOCOM, 2012, pp. 2731–2735. | - |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/98623 | - |
| dc.description.abstract | IEEE 802.11 標準提出了目標喚醒時間(Target Wake Time, TWT)作為重要的省電機制,透過排程站台(STAs)的喚醒時間來接收封包,並在其他時間進入休眠模式(Doze State)以節省電力。雖然TWT可顯著降低能源消耗並緩解頻道競爭,但其對資訊新鮮度(information freshness)的影響尚未得到充分探討,而資訊新鮮度正是即時性和物聯網應用中的關鍵需求之一。尤其是用來量化數據即時性的資訊年齡(Age of Information, AoI),在現有的TWT分析中鮮少被考量。
據作者所知,本研究首次針對各種TWT設定,推導出資訊年齡(AoI)的期望值、峰值資訊年齡(peak AoI)的期望值,以及平均功耗之解析閉合式解。透過模擬驗證後的分析結果顯示,在固定喚醒比例(awake ratio)的情況下,提高喚醒頻率(亦即將偵聽間隔LI設為1)能有效降低資訊年齡的期望值與峰值資訊年齡,且不會增加功耗。這些結果提供了調整TWT參數的具體指引,並為改善網路效能提供了有價值的參考依據。 | zh_TW |
| dc.description.abstract | The IEEE 802.11 standard introduces Target Wake Time (TWT) as a crucial power-saving mechanism that schedules the wake-up times of stations (STAs) for receiving packets, while the remaining time is spent in a Doze State to conserve power. Although TWT significantly reduces energy consumption and mitigates channel contention, its impact on information freshness—a key requirement for real‑time and IoT applications—remains underexplored. In particular, Age of Information (AoI), which quantifies the timeliness of received data, has rarely been considered in existing TWT analyses. To the best of the authors’ knowledge, this work is the first to analytically derive closed-form expressions for expected AoI, expected peak AoI, and average power consumption under various TWT configurations. The analysis—validated by simulation—shows that frequent wake-ups (i.e., setting the listen interval LI to 1) yield the lowest expected and peak AoI without increasing power usage for a given awake ratio. These findings provide actionable guidelines for tuning TWT parameters and offer valuable insights for improved network performance. | en |
| dc.description.provenance | Submitted by admin ntu (admin@lib.ntu.edu.tw) on 2025-08-18T01:07:13Z No. of bitstreams: 0 | en |
| dc.description.provenance | Made available in DSpace on 2025-08-18T01:07:13Z (GMT). No. of bitstreams: 0 | en |
| dc.description.tableofcontents | 口試委員會審定書 i
致謝 ii 摘要 iii Abstract iv Contents v List of Figures vii List of Tables ix Chapter 1. Introduction 1 Chapter 2. Related Work 3 Chapter 3. Background 7 3.1 Target Wake Time(TWT) 7 3.2 Age of Information(AoI) 8 Chapter 4. System Model 11 Chapter 5. Analytical Model 13 5.1 Analysis of Expected AoI 13 5.1.1 Update Occurs Within the Same SP 15 5.1.2 Update Occurs Within a Future SP 16 5.2 Analysis of Expected Peak AoI 19 5.3 Analysis of Power Consumption 19 Chapter 6. Simulation Results 21 6.1 Simulation Settings 21 6.2 Observations on Listen Interval 22 6.3 Observations on TWT SP 22 6.4 Observations on Constant Awake Ratio 24 6.5 Tradeoff between AoI, Peak AoI, and Power Consumption 26 Chapter 7. Discussion 31 Chapter 8. Conclusions and Future Directions 37 Bibliography 39 | - |
| dc.language.iso | en | - |
| dc.subject | Wi-Fi | zh_TW |
| dc.subject | IEEE 802.11 | zh_TW |
| dc.subject | 資訊新鮮度 | zh_TW |
| dc.subject | 節能 | zh_TW |
| dc.subject | 目標喚醒時間 | zh_TW |
| dc.subject | TWT | en |
| dc.subject | power saving | en |
| dc.subject | AoI | en |
| dc.subject | Wi-Fi | en |
| dc.subject | IEEE 802.11 | en |
| dc.title | IEEE 802.11 資訊新鮮度與能源效率的權衡分析:目標喚醒時間機制之資訊年齡效能分析 | zh_TW |
| dc.title | Information Freshness and Energy Efficiency Tradeoffs in IEEE 802.11: Age of Information Performance Analysis of Target Wake Time Mechanism | en |
| dc.type | Thesis | - |
| dc.date.schoolyear | 113-2 | - |
| dc.description.degree | 碩士 | - |
| dc.contributor.oralexamcommittee | 陳彥賓;巫芳璟;柯拉飛 | zh_TW |
| dc.contributor.oralexamcommittee | Yan-Bin Chen;Fang-Jing Wu;Rafael Kaliski | en |
| dc.subject.keyword | IEEE 802.11,Wi-Fi,目標喚醒時間,節能,資訊新鮮度, | zh_TW |
| dc.subject.keyword | IEEE 802.11,Wi-Fi,TWT,power saving,AoI, | en |
| dc.relation.page | 43 | - |
| dc.identifier.doi | 10.6342/NTU202502229 | - |
| dc.rights.note | 未授權 | - |
| dc.date.accepted | 2025-08-11 | - |
| dc.contributor.author-college | 電機資訊學院 | - |
| dc.contributor.author-dept | 電機工程學系 | - |
| dc.date.embargo-lift | N/A | - |
| 顯示於系所單位: | 電機工程學系 | |
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