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研究生： 鄭錦明
Jin-Ming Zheng
論文名稱： 第五代行動網路中大量機器類型通訊的分組非正交多路存取方法
A Grouping Non-Orthogonal Multiple Access Method for Massive Machine-Type Communication in 5G Networks
指導教授： 黎碧煌
Bih-Hwang Lee
口試委員: 黎碧煌
Bih-Hwang Lee
馬奕葳
Yi-Wei Ma
陳俊良
Jiann-Liang Chen
鍾添曜
Tein-Yaw Chung
學位類別： 碩士
Master
系所名稱： 電資學院 - 電機工程系
Department of Electrical Engineering
論文出版年： 2021
畢業學年度： 109
語文別： 英文
論文頁數： 102
中文關鍵詞： 物聯網 、機器類型通訊 、隨機存取 、設備對設備通訊 、非正交多路存取
外文關鍵詞： Internet of Things, Machine type Communication, Random Access, Device-to-Device Communication, Non-Orthogonal Multiple Access
相關次數： 點閱：221  下載：1 
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    • 隨著物聯網(Internet of Things; IoT)的蓬勃發展，各式各樣的相關應用落實在生活中。像是智慧城市、智慧工廠、車聯網(Vehicles to Everything; V2X)等等的應用。因此物聯網設備將以指數型的增長。第三代合作夥伴計畫(Third Generation Partnership Project Agreement; 3GPP)因應物聯網的發展，提出了機器類型通訊(Machine -Type Communication; MTC)的標準，並成為了網路應用發展的關鍵技術。在第五代行動通訊網路架構下，當設備要傳送資料前，必須採取隨機(Random Access; RA)程序向基地台(Base Station; BS)建立連線。由於實體隨機存取通道 (Physical Random Access Channel; PRACH)和實體上行共享通道(Physical Uplink Shared Channel; PUSCH) 的資源有限。當大量的設備需要進行存取時，將會造成隨機存取碰撞機率大幅提升、頻道資源不足，最終導致網路擁塞，造成設備存取成功率下降。
    本論文針對大量機器類類型通訊設備(Machine-Type Communication Devices; MTCDs)隨機存取提出了一種解決方案。透過設備對設備(Device-to-Device; D2D)分組架構，並結合功率域非正交多路存取(Non-Orthogonal Multiple Access; NOMA)的概念。透過組長(Group Head; GH)指派隨機存取機會(Random Access Opportunity; RAO)、前導碼(Preamble)、設備用於訊息3的功率指標(Power Indicator; PI)。由模擬結果顯示所提出的機制將有效改善隨機存取碰撞問題，並提高頻道資源的利用率。並考慮到在智慧城市的環境裡，設備位置分布不同的情況下，該機制依然可以保持較短的時間解決網路的擁塞，大幅的提高系統的效能。

    With the vigorous development of the Internet of Things (IoT), it has been widely applied in our life, such as smart cities, smart factories, Vehicles to Everything (V2X), and so on. Because of these applications, IoT devices would grow exponentially. In response to the development of IoT, the Third Generation Partnership Project Agreement (3GPP) proposed the Machine-Type Communication (MTC) standard, which has become a key technology for the network applications. Under the fifth generation of mobile communication network architecture, the device has to adopt the Random Access (RA) procedure to establish a connection to the base station when it transmit data. Due to the limited resources of the Physical Random Access Channel (PRACH) and Physical Uplink Shared Channel (PUSCH), when a massive amount of devices need to be accessed, the probability of RA collisions would greatly increase, channel resources become insufficient, and eventually lead to network congestion and a decrease in the success rate of device access.
    This work proposes a solution for the random access of massive Machine-Type Communication Devices (MTCDs), combined with the power domain Non-Orthogonal Multiple Access (NOMA) concept with the Device to Device grouping architecture. Assign Random Access Opportunity (RAO) and preamble through the Group Head, and the device be used for the Power Indicator (PI) of Msg3. The simulation results show that the above mechanism can well improve the RA collision problem and increase the utilization of channel resources. Considering that the devices are distributed in different locations in the smart city, the mechanism can still solve the network congestion in a short time, and greatly improve the efficiency of the system.

    摘要 Abstract Acknowledgments Table of Contents List of Abbreviations List of Notations List of Figures List of Tables Chapter 1 Introduction 1.1 Research Motivation 1.2 Contributions 1.3 Organization of Thesis Chapter 2 Background and Related Works 2.1 Cellular Network Overview 2.1.1 5G New Radio 2.1.2 Specification Introduction 2.1.3 Random Access Procedure 2.1.4 PRACH Configuration Index 2.1.5 Random Access Response MAC PDU Structure 2.1.6 RA Backoff Mechanism 2.1.7 Non-Orthogonal Multiple Access (NOMA) 2.2 Machine Type Communication Overview 2.2.1 MTCD Features 2.2.2 MTC Access type 2.3 Device to Device Communication Overview 2.3.1 D2D Connection Types 2.3.2 D2D Related System Information 2.4 Related Work 2.5 Problem Description Chapter 3 Grouping NOMA Method 3.1 Research Method 3.2 Initial Situation Setting 3.3 D2D Communication Model 3.4 Proposed RA Procedure 3.4.1 Preamble Assignment 3.4.2 Group Member Procedure 3.4.3 Group Head Procedure 3.4.4 gNB Procedure 3.4.5 MAC RAR Format Chapter 4 System Simulation 4.1 Simulation Environment and Parameters 4.2 Assumptions of Simulation 4.3 Effectiveness Evaluation Project 4.4 Analysis and Comparison of Simulation Results 4.4.1 General scenario 10,000 MTCDs simulation 4.4.2 General scenario 30,000 MTCDs simulation 4.4.3 General scenario 50,000 MTCDs simulation 4.4.4 Extreme scenarios 100,000 MTCDs simulation 4.4.5 Extreme scenarios 150,000 MTCDs simulation 4.4.6 Compare the effectiveness of the proposal-Grouping NOMA mechanism and the Preamble Allocation mechanism under MTCDs different position distributions. Chapter 5 Conclusions and Future Work Reference

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