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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 闕志達 | |
dc.contributor.author | Nai-Hsuan Huang | en |
dc.contributor.author | 黃乃軒 | zh_TW |
dc.date.accessioned | 2021-06-17T06:26:56Z | - |
dc.date.available | 2023-08-21 | |
dc.date.copyright | 2018-08-21 | |
dc.date.issued | 2018 | |
dc.date.submitted | 2018-08-16 | |
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dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/72170 | - |
dc.description.abstract | 大規模機器通訊 (mMTC) 是第五代 (5G) 無線通訊系統三大應用場景之一,機器通訊的特色在於資料量小,屬於偶發性流量 (Sporadic Traffic),是一種以上行為主的應用場景;上行免許可非正交多工存取 (Uplink Grant-Free NOMA) 是目前在文獻中與3GPP會議中備受關注的一項技術,這項技術主要將以往4G使用者與基地台之間的排程過程去除,並且讓多個使用者共享時頻資源,帶來的好處是頻譜使用效益的增加,延遲的減緩 (Latency),和訊號傳送成本的減少;但因為排程過程的去除,使得基地台無法得知使用者資訊,因此在解碼以前必須要先做用戶偵測 (User Activity Detection, UAD) 來偵測有在傳送訊號的使用者,才可以進行解碼。本論文的研究目標在於提高UAD的準確度,項目包含領航序列碼 (Pilot Sequence) 的設計與UAD演算法的開發。
第三章中,介紹了現有文獻在UAD議題上的做法,透過模擬與分析來討論現有文獻的不足之處,並且提出了預強調領航序列碼 (Pre-emphasis Pilot Sequence) 的設計來補足現有文獻的不足之處。 第四章中,考量到一個具有時變效應的通道模型,在這樣的通道模型下只用預強調領航序列碼是不足夠的,因此提出一個可適性列表最大期望演算法 (Adaptive List Expectation Maximization, ALEM),經由模擬證實ALEM是一個對於通道變化具有適應性的一套UAD演算法,比起現有現有文獻演算法擁有更高的精準度與通道變異上的可適性。 在論文的最後一章,提出了一個低複雜度ALEM (Low-complexity ALEM, LALEM),LALEM比起ALEM可以節省大約20倍的運算時間,但效能和ALEM幾乎一樣;同時分析現有演算法的運算量,以不同長度的領航序列碼和使用者數量來視覺化演算法的可擴展性 (Scalability),結論是LALEM擁有最好的效能並且擁有良好的擴展性。 | zh_TW |
dc.description.provenance | Made available in DSpace on 2021-06-17T06:26:56Z (GMT). No. of bitstreams: 1 ntu-107-R05943028-1.pdf: 6331531 bytes, checksum: bce997f2ab13a296b36302c5f1b21245 (MD5) Previous issue date: 2018 | en |
dc.description.tableofcontents | 致謝 i
摘要 iii Abstract v 目錄 vii 圖目錄 xi 表目錄 xv 第一章 緒論 1 1.1 研究背景 1 1.2 研究動機 3 1.3 用戶偵測研究現況 5 1.4 論文組織與貢獻 5 第二章 5G-NR機器通訊上行環境介紹 7 2.1 非正交多工存取 (NOMA) 7 2.2 上行免許可傳輸 (Uplink Grant-free Transmission) 8 2.3 機器通訊的資料型態 (Machine Type Communication Traffic Type) 9 2.4 上行接收機架構 (Uplink Receiver Architecture) 10 第三章 領航序列設計 11 3.1 現有文獻介紹與分析 11 3.1.1 訊號模型 11 3.1.2 DGOMP [20,33] 15 3.1.3 SBL [21,22,31] 19 3.1.4 FOCUSS [19,36,37] 24 3.1.5 現有文獻之模擬與分析 26 3.2 本論文提出的領航序列設計 33 3.2.1 領航序列設計之模擬與分析 35 3.3 第三章總結 39 第四章 用戶偵測設計 41 4.1 考量通道時變因素的訊號模型 41 4.2 本論文所提出的用戶偵測設計 43 4.2.1 用戶偵測之演算法設計 43 4.2.2 用戶偵測之架構 47 4.3 用戶偵測設計之模擬與分析 58 4.4 第四章總結 63 第五章 用戶偵測之低複雜度架構設計 65 5.1 低複雜度架構設計 65 5.2 低複雜度用戶偵測設計之模擬與分析 69 5.3 複雜度分析 72 5.4 第五章總結 81 第六章 結論與展望 83 附錄 85 附錄一 Complexity Analysis of LALEM 85 附錄二 Complexity Analysis of DGOMP 93 附錄三 Complexity Analysis of SBL 95 附錄四 Complexity Analysis of FOCUSS 96 附錄五 Complexity of Log2 97 附錄六 Uncorrelated channel variation rate 101 參考文獻 103 | |
dc.language.iso | zh-TW | |
dc.title | 5G網路下免許可傳輸非正交多工存取之用戶偵測與領航序列碼設計 | zh_TW |
dc.title | User Activity Detection and Pilot Sequence Design for Uplink Grant-free NOMA in 5G Networks | en |
dc.type | Thesis | |
dc.date.schoolyear | 106-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 賴以威,王奕翔 | |
dc.subject.keyword | 免許可傳輸,非正交多工存取,用戶偵測,領航序列碼設計,時變通道,可適性,最大期望演算法, | zh_TW |
dc.subject.keyword | Grant-Free transmission,Non-orthogonal Multiple Access,User Activity Detection,Pilot Sequence Design,Time-Variant Channel,Adpative,Expectation Maximization, | en |
dc.relation.page | 107 | |
dc.identifier.doi | 10.6342/NTU201803808 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2018-08-17 | |
dc.contributor.author-college | 電機資訊學院 | zh_TW |
dc.contributor.author-dept | 電子工程學研究所 | zh_TW |
顯示於系所單位: | 電子工程學研究所 |
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