請用此 Handle URI 來引用此文件:
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/92927
完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 貝蘇章 | zh_TW |
dc.contributor.advisor | Soo-Chang Pei | en |
dc.contributor.author | 謝佳茵 | zh_TW |
dc.contributor.author | Chia-Yin Hsieh | en |
dc.date.accessioned | 2024-07-05T16:08:53Z | - |
dc.date.available | 2024-07-06 | - |
dc.date.copyright | 2024-07-05 | - |
dc.date.issued | 2024 | - |
dc.date.submitted | 2024-06-24 | - |
dc.identifier.citation | [1] A.J.E.M. Janssen, Charlie O’Brien and Peter Meehan. ”The Zak Transform: A Sig- nal Transform for Sampled Time-Continuous Signals”. Philips Journal of Research, 43(1):23 – 69, 1988.
[2] Helmut Bolcskei and Franz Hlawatsch.”Discrete Zak Transforms, Polyphase Transforms, and Application”. IEEE Transactions on Signal Processing, 45(4):851 – 866, 1997. [3] Andrzej K. Brodzik. ”Characterization of Zak Space Support of A Discrete Chirp”. IEEE Transactions On Information Theory, 53(6):2190 – 2203, 2007. [4] Andrzej K. Brodzik and Richard Tolimieri. ” Bat Chirps with Good Properties: Zak Space Construction of Perfect Polyphase Sequences”. IEEE Transactions on Information Theory, 55(4):1804 – 1814, 2009. [5] Zhao Zhao, Malte Schellmann, Xitao Gong, Qi Wang, Ronald Böhnke and Yan Guo. ” Pulse Shaping Design for OFDM Systems”. Wireless Communications and Networking, (74):11024–11037, 2017. [6] Said Lmai, Arnaud Bourre, Christophe Laot and Sébastien Houcke. ”Advantages of Pulse-Shaping Applied to OFDM Systems over Underwater Acoustic Channels”. IEEE Conference, page 1–7, 2012. [7] Wenqian Shen, Linglong Dai, Jianping An, Pingzhi Fan and Robert W. Heath, Jr. ”Channel Estimation for Orthogonal Time Frequency Space (OTFS) Massive MIMO”. IEEE Transactions On Signal Processing, 67(16):4204 – 4217, 2019. [8] Franz Lampel, Alex Alvarado and Frans M.J. Willems.”Orthogonal Time Frequency Space Modulation: A Discrete Zak Transform Approach”. eess.SP, 1(2106.12828):1 – 13, 2021. [9] Wenqian Shen, Linglong Dai, Jianping An, Pingzhi Fan and Robert W. Heath, Jr. ” New Delay Doppler Communication Paradigm in 6G Era: A Survey of Orthogonal Time Frequency Space (OTFS)”. cs.IT, 1(2211.12955):1 – 26, 2023. [10] Yongzhi Wu, Chong Han and Zhi Chen. ”DFT-Spread Orthogonal Time Frequency Space System with Superimposed Pilots for Terahertz Integrated Sensing and Communication”. IEEE Transactions On Wireless Communications, 22(11):7361 – 7376, 2023. [11] Chao Xu, Xiaoyu Zhang, Periklis Petropoulos, Shinya Sugiura, Robert G. Maun- der, Lie-Liang Yang, Zhaocheng Wang, Jinghong Yuan, Harald Haas and Lajos Hanzo. ”Optical OTFS is Capable of Improving the Bandwidth-, Power- and Energy- Efficiency of Optical OFDM”. IEEE Transactions on Communications, pages 1 – 15, 2023. [12] Hai Lin and Jinhong Yuan.”Orthogonal Delay-Doppler Division Multiplexing Modulation”. IEEE Transactions On Wireless Communications, 21(12):11024–11037, 2022. [13] Hai Lin and Jinhong Yuan. ” Multicarrier Modulation on Delay-Doppler Plane: Achieving Orthogonality with Fine Resolutions”. IEEE International Conference on Communications, page 2417–2422, 2022. | - |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/92927 | - |
dc.description.abstract | 傳統的傅立葉轉換以其將信號轉換為對應頻譜的能力而聞名,但追蹤頻譜的時間演變卻存在挑戰。薩克時頻轉換是一種時頻分析的工具,可使信號從時間域轉換到時間-頻率域。與傅立葉轉換不同,薩克時頻轉換允許對信號頻率在時間上的動態變化進行更詳細的檢查。其線性特性是一個突出的特點,可防止在時頻分析中常見的干擾,如交叉項的出現。這種線性特性能夠精確地隔離信號,突顯了它在時頻信號處理應用中的重要性。
在我們探索薩克時頻轉換應用的過程中,我們發現了兩種不同的應用。首先,在利用完美序列集時,薩克時頻轉換使精確的時間-頻率分析成為可能,確保信號僅在其具有重要性的地方顯現,從而減輕了干擾問題。其次,在正交時頻空間的通信應用中,通過將薩克時頻轉換納入正交時頻空間系統,相較於傳統方法,我們不僅保持了相等的輸入-輸出關係,還減少了計算複雜度。 | zh_TW |
dc.description.abstract | The Fourier transform is renowned for its ability to translate signals into their corresponding spectrum, yet tracking the temporal evolution of this spectrum presents challenges. Enter the Zak transform, a valuable tool facilitating the translation of signals from the time domain to the time-frequency domain. Unlike the Fourier transform, the Zak transform allows for a more detailed examination of dynamic changes in signal frequencies over time. Its linearity is a standout feature, preventing the emergence of interference, such as cross terms, commonly encountered in time-frequency analysis. This linearity, coupled with its ability to isolate signals precisely, underscores its significance in signal processing applications.
In our exploration of the Zak transform's applications, we've discovered its efficacy in two distinct contexts. Firstly, when leveraging perfect sequence sets, the Zak transform enables precise time-frequency analysis, ensuring that signals only manifest where they hold significance, thereby mitigating interference issues. Secondly, in communication applications like Orthogonal Time Frequency Space (OTFS), the Zak transform proves invaluable. By incorporating it into OTFS systems, we not only maintain equivalent input-output relationships but also reduce computational complexity compared to conventional methods. | en |
dc.description.provenance | Submitted by admin ntu (admin@lib.ntu.edu.tw) on 2024-07-05T16:08:52Z No. of bitstreams: 0 | en |
dc.description.provenance | Made available in DSpace on 2024-07-05T16:08:53Z (GMT). No. of bitstreams: 0 | en |
dc.description.tableofcontents | Acknowledgements i
中文摘要 ii Abstract iii Contents v List of Figures vii List of Tables xii Chapter 1 Introduction 1 Chapter 2 Definitions of The Zak Transform 3 2.1 The Continuous-time Zak Transform 4 2.2 The Discrete-time Zak Transform 5 2.3 The Discrete Zak Transform 6 2.4 The Finite Zak Transform 7 Chapter 3 Properties of The Zak Transform 8 3.1 Time Frequency Analysis 9 3.2 Linearity 9 3.3 Simulation Results 12 3.3.1 Simulation Results for Mono-Component Signal 12 3.3.2 Simulation Results for Multi-Component Signal 18 Chapter 4 Communication Applications of The Zak Transform 25 4.1 Perfect Sequence Set 26 4.1.1 Zak Space Conditions 26 4.1.2 Composition and Properties of Perfect Sequence Sets 39 4.1.3 Perfect Chirp Set 44 4.1.4 Simulation Results 47 4.2 Orthogonal Time Frequency Space(OTFS) 50 4.2.1 Pulse Shaping Orthogonal Frequency Division Multiplexing (OFDM) 51 4.2.2 Orthogonal Time Frequency Space (OTFS) SISO System 52 4.2.3 Orthogonal Time Frequency Space (OTFS) Massive MIMO System 58 4.2.4 DZT-based Orthogonal Time Frequency Space (OTFS) 62 4.2.5 DFT-Spread Orthogonal Time Frequency Space (DFT-s-OTFS) System 65 4.2.6 Orthogonal Delay-Doppler Division Multiplexing (ODDM) 68 4.2.7 Simulation Results 71 Chapter 5 Conclusions 83 References 84 | - |
dc.language.iso | en | - |
dc.title | 薩克時頻轉換與其在通訊上的應用 | zh_TW |
dc.title | Zak Time-Frequency Transform and Its Communication Applications | en |
dc.type | Thesis | - |
dc.date.schoolyear | 112-2 | - |
dc.description.degree | 碩士 | - |
dc.contributor.coadvisor | 丁建均 | zh_TW |
dc.contributor.coadvisor | Jian-Jiun Ding | en |
dc.contributor.oralexamcommittee | 杭學鳴;吳家麟;鍾國亮 | zh_TW |
dc.contributor.oralexamcommittee | Hsueh-Ming Hang;Ja-Ling Wu;Kuo-Liang Chung | en |
dc.subject.keyword | 薩克時頻轉換,時頻轉換,完美序列集,正交時頻空間, | zh_TW |
dc.subject.keyword | Zak time-frequency transform,Time-frequency transform,Perfect sequence set,OTFS system, | en |
dc.relation.page | 86 | - |
dc.identifier.doi | 10.6342/NTU202401211 | - |
dc.rights.note | 同意授權(限校園內公開) | - |
dc.date.accepted | 2024-06-24 | - |
dc.contributor.author-college | 電機資訊學院 | - |
dc.contributor.author-dept | 電信工程學研究所 | - |
顯示於系所單位: | 電信工程學研究所 |
文件中的檔案:
檔案 | 大小 | 格式 | |
---|---|---|---|
ntu-112-2.pdf 目前未授權公開取用 | 6.19 MB | Adobe PDF | 檢視/開啟 |
系統中的文件,除了特別指名其著作權條款之外,均受到著作權保護,並且保留所有的權利。