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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 謝宏昀 | |
| dc.contributor.author | CHIEN-HUNG LIN | en |
| dc.contributor.author | 林建宏 | zh_TW |
| dc.date.accessioned | 2021-06-17T06:19:43Z | - |
| dc.date.available | 2021-08-21 | |
| dc.date.copyright | 2018-08-21 | |
| dc.date.issued | 2018 | |
| dc.date.submitted | 2018-08-20 | |
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/72026 | - |
| dc.description.abstract | LTE於非授權頻譜的使用已經在這幾年被廣泛的討論，其中Licensed-Assisted Access (LAA) 更是討論的重點之一，LAA使用Listen-Before-Talk (LBT)的技術來達到與其他網路通訊技術共存，在多數研究中著重於用模擬對整體系統的分析，少數研究考量數學模型的架構。在本篇論文中，我們提出包含混合式自動重送請求的LAA數學模型，此外我們也對模型中的機率來重新定義以達到較準確的分析結果，因為LAA 基地台可以同時服務多個使用者，且不是所有封包都可以同時被成功接收，因此需要新的評斷標準來決定傳遞狀況是否成功與競爭視窗的大小。根據3GPP的文件指出，競爭視窗的更新規則需要依照混合式自動重送請求，如果有大於80%的NACK於混合式自動重送請求在下行burst的的第一個subframe中，然而現存的LAA數學模型並沒有考量到混合式自動重送請求，因此我們考量混合式自動重送請求並提出一個新的LAA數學模型。接著我們依照標準中LBT的流程圖用MATLAB去模擬出結果，並用此結果去驗證我們的LAA數學模型，我們的LAA數學模型在大多數情況下可以達到70%以上的準確率，相對其他學模型高出許多，此外我們也分析混合式自動重送請求的影響，混合式自動重送請求的啟動與否對於utility與throughput的影響很小，差距在1%以內，但是在丟失封包的比例上，有混合式自動重送請求的影響會比較明顯。最後我們也討論了各個混合式自動重送請求中各個參數的影響。 | zh_TW |
| dc.description.abstract | LTE in unlicensed band has been discussed in recent years and named Licensed- Assisted Access (LAA) which uses Listen-Before-Talk (LBT) mechanism. There are lots of works which only focus on system simulation, but few of them concern about analytical model. In this thesis, we probe into the measure of how to build an analytical model to evaluate the performance of LAA with Hybrid Automatic Repeat reQuest (HARQ) feedback. Therefore, we create a proposed Markov chain model and use it to help us to evaluate the performance of LAA with HARQ feed- back. Besides, we re-define some definition of probability to measure the accurate performance. In addition, because each LAA evolved NodeB can serve many users at the same time and some transmission would not be successful, it has to use new way to decide whether total transmission is successful or not and how to set the contention window size (CWS). According to 3GPP document, the CWS updated rule of LAA should be based on HARQ feedback. The CWS is increased if at least 80% of the HARQ-ACK feedback values for the first subframe of a down- link burst are NACK. The present papers still do not consider HARQ feedback in analytical model. Therefore, We take HARQ feedback into consideration in our proposed LAA Markov chain model. Then, we use MATLAB to simulate LAA protocol based on the flowchart in standard. We use MATLAB simulation results to verify our LAA Markov chain model with HARQ feedback. Our LAA Markov chain model can get higher than 70% accuracy to show the LAA performance in most situation which is better than other model. Moreover, we also show the effect of HARQ feedback. The difference between value with HARQ feedback and value without HARQ feedback is small for utility and throughput (smaller than 1%), but it is much large for percentage of dropped packet (90%). In the end, we discuss the relationship between parameter of HARQ feedback. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-17T06:19:43Z (GMT). No. of bitstreams: 1 ntu-107-R05942052-1.pdf: 4990749 bytes, checksum: a055e7f395ffff8d5f55ef6296e818c1 (MD5) Previous issue date: 2018 | en |
| dc.description.tableofcontents | ABSTRACT .................................. ii
LIST OF TABLES .............................. v LIST OF FIGURES ............................. vi CHAPTER 1 INTRODUCTION .................... 1 CHAPTER 2 BACKGROUND AND RELATED WORK . . . . . 5 2.1 WiFi Markov Chain Model ...................... 5 2.1.1 Enhanced distributed channel access. . . . . . . . . . . . . 5 2.1.2 802.11e analytical model ................... 7 2.2 LBT Introduction ........................... 15 2.2.1 LBT mechanism........................ 15 2.2.2 LAA priority.......................... 18 2.2.3 LAA Markov chain model................... 19 2.3 HARQ Feedback............................ 20 2.3.1 HARQ mechanism....................... 20 2.3.2 HARQ feedback probability.................. 21 2.3.3 3GPP updated rule based on HARQ feedback . . . . . . . 22 2.4 RelatedWork ............................. 23 CHAPTER 3 ANALYTICAL MODEL WITH HARQ FEEDBACKS 30 3.1 LAA Cat.4 LBT procedure ...................... 30 3.2 Discrete Time Markov Chain Model ................. 31 3.3 Transition Probabilities........................ 36 3.3.1 Idle stage............................ 36 3.3.2 ICCA stage .......................... 37 3.3.3 Frozen stage .......................... 37 3.3.4 ECCA in ECCA stage..................... 37 3.3.5 Back-off stage ......................... 38 3.3.6 Pre-transmission stage .................... 38 3.3.7 Successful transmission stage and HARQ feedback . . . . . 39 3.3.8 Collision stage......................... 40 3.4 System Equations ........................... 40 3.5 Probability Definition......................... 43 3.5.1 Collision probability...................... 43 3.5.2 Busy probability during back-off stage . . . . . . . . . . . . 45 3.5.3 Busy probability at state (−1,0,A) . . . . . . . . . . . . . 46 3.5.4 Busy probability during ICCA stage except (−1, 0, A) . . . 46 3.5.5 Probability of that NACK percentage of HARQ feedbacks is lower than α......................... 47 3.6 Solving System of Equations ..................... 48 3.7 Definition of Performance Parameters ................ 50 CHAPTER 4 EVALUATION RESULTS AND DISCUSSIONS . 54 4.1 Protocol and Definition of Probability in MATLAB . . . . . . . . 54 4.2 Comparison for Varying Traffic Arrival Rate . . . . . . . . . . . . 57 4.3 Comparison for Varying Number of eNBs . . . . . . . . . . . . . . 65 4.4 Effect of HARQ Feedbacks ...................... 70 4.4.1 Impact of traffic arrival rate and pF . . . . . . . . . . . . . 70 4.4.2 Impact of traffic arrival rate and threshold . . . . . . . . . 71 4.4.3 Impact of traffic arrival rate and NH . . . . . . . . . . . . . 72 4.4.4 Impact of pF and NH ..................... 75 4.4.5 Impact of threshold and NH ................. 76 CHAPTER 5 CONCLUSION AND FUTURE WORK . . . . . . 79 REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 | |
| dc.language.iso | zh-TW | |
| dc.subject | LAA | zh_TW |
| dc.subject | 馬可夫鍊 | zh_TW |
| dc.subject | 混合式自動重送請求機制 | zh_TW |
| dc.subject | LAA | en |
| dc.subject | Markov chain | en |
| dc.subject | HARQ feedback | en |
| dc.title | 考慮混合式自動重送請求機制之LAA模型分析與效能評估 | zh_TW |
| dc.title | Analysis and Evaluation of Markov-based Modeling for Licensed-Assisted Access with Hybrid Automatic Repeat Request Feedback | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 106-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 周俊廷,林風 | |
| dc.subject.keyword | LAA,馬可夫鍊,混合式自動重送請求機制, | zh_TW |
| dc.subject.keyword | LAA,Markov chain,HARQ feedback, | en |
| dc.relation.page | 81 | |
| dc.identifier.doi | 10.6342/NTU201803928 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2018-08-20 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 電信工程學研究所 | zh_TW |
| 顯示於系所單位： | 電信工程學研究所 | |
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