機器類型通訊（MTC）服務是5G/B5G網路的重要應用之一。一般而言，機器類型通訊可以分為兩類：巨量型機器類型通訊（mMTC）和超高可靠低延遲機器類型通訊（uMTC）。本論文分別探討這兩類機器類型通訊中的應用服務：窄頻物聯網，NB-IoT（mMTC）和蜂巢式車間通訊，C-V2V（uMTC），並基於3GPP NB-IoT和C-V2V規範，提出了新的機制來提高NB-IoT的設備壽命和C-V2V的通訊可靠性，從而為未來6G無線網路做出貢獻。
NB-IoT是mMTC中的一項重要服務。其系統的關鍵要求包括極低的設備成本和極低的設備能耗，並且由於NB-IoT系統中的設備通常使用不可充電的電池，因此NB-IoT系統的目標是盡可能地提高電池壽命。本論文提出了一種用於mMTC的NB-IoT系統的最佳中繼傳輸節能調度機制。這個調度機制會選擇最佳中繼節點配對組合以最小化NB-IoT系統整體的能耗。模擬的結果顯示，與傳輸節點（transmitting UE）直接對基地台傳輸相比，使用最佳中繼傳輸機制在傳輸節點密度為0.1 ~ 0.5時，其NB-IoT系統整體的能耗能夠降低到32.8% ~ 62.7%。此外在NB-IoT系統使用10年之後，使用最佳中繼傳輸機制其節點的平均剩餘電量為不使用此機制的1.89倍。
就C-V2V而言，關於車輛行車安全需要高可靠低延遲的通訊服務。所以在C-V2V中如何避免傳輸干擾以提高封包的接收成功率，進而實現極可靠的通訊是其中一項重要的議題；並且為了實現低延遲通訊，首先我們減少信令（signaling）數量以減輕基地台（eNB/gNB）的負擔，之後將資源分配信令由基地台卸載（offload）到群集頭（cluster head）進而降低通訊延遲。本論文為uMTC的C-V2V通訊提出了一種基於動態區域的資源分配方案。基於動態區域的資源分配方案將車輛自適應地劃分為幾個集群，並將無線電資源劃分為兩個不同的資源池。相鄰群集使用不同的無線電資源池，以避免同頻干擾並提高通訊的可靠性。模擬的結果顯示，在高速公路的環境下，本論文提出的基於動態區域的資源分配方案，在距離傳輸車輛300 ~ 320公尺範圍中的所有接收車輛其平均封包成功接收率高達86.7%，符合3GPP標準的預期(>80%) 並且與完全集中式窮舉法相比差距不大；此外使用我們的方案，平均基地台信令數量能夠降低30.9%。

Machine-type communications (MTC) are useful and prevalent in various applications of the 5G/B5G wireless networks. In general, the 3GPP MTC can be categorized into two types: the massive MTC (mMTC) and the ultra-reliable and low-latency MTC (uMTC). The uMTC is also referred to as Ultra-Reliable and Low-Latency Communications (URLLC) when the communication is emphasized. Narrowband Internet of Things (NB-IoT) is an important service in mMTC. Transmitting at a very low data rate, an NB-IoT device is required to communicate with base station in a very long range by multiple repetitions of a data unit in a transmission. Due to the often non-rechargeable battery in an NB-IoT device, one of the main engineering issue in a NB-IoT system is to reduce energy consumption and prolong the lifetime of a NB-IoT device as long as possible. The Cellular Vehicle-to-Vehicle (C-V2V) communication is one of the important services in uMTC, in particular, when the C-V2V communication is related to driving safety. Avoiding co-channel interference can improve packet receiving rates (PRR) to achieve a more reliable communication in C-V2V. Besides, to achieve low-latency communications, we need to reduce both computation and signaling overheads in eNB/gNB by offloading scheduling computation and decisions from eNB/gNB.
This dissertation contains two parts each of which addresses the issues in NB-IoT and C-V2V mentioned in the above. In the first part, an optimal one-hop UE-to-Network (gNB) relay scheme is proposed to save energy consumption in the NB-IoT system. By adequate reduction, an optimal relay-node-chosen problem is transferred into an optimal matching problem and could be solved effectively in polynomial time. By the proposed scheme, the system could save energy consumption from 32.8% to 62.7%, when the density of the transmitting UEs is from 0.1 to 0.5. After 10 year operation, with the proposed optimal relaying scheme, the average residual energy of a NB-IoT UE is expected to be 1.89 times as much as that in the system without relaying scheme.
In the second part, a dynamic region-based resource allocation scheme for C-V2V communications of uMTC is proposed to adaptively divides vehicles into several clusters each of which is assigned by one of two pre-designed radio resource pools. Adjacent clusters will be assigned different radio resource pools to avoid co-channel interference and increase communication reliability. By extensive simulations, it is shown that under the 3GPP freeway simulation setup, the proposed clustering and scheduling scheme can achieve a PRR at 86.7%, that is greater than the 3GPP PRR requirement at 80%, but also largely reduces the signaling overhead to only 30.9% compared to the C-V2V centralized scheduling scheme.
To sum up, in this dissertation, based on the 3GPP NB-IoT (mMTC) and C-V2V (uMTC) specifications, new mechanisms to improve the device lifetime in NB-IoT and communication reliability in C-V2V are proposed in order to contribute to future 6G wireless networks.

摘要 I
ABSTRACT II
誌謝 IV
TABLE OF CONTENTS V
TABLE INDEX VII
FIGURE INDEX VIII
NOTATION X
Chapter 1. Introduction 1
1.1 Motivation of the research 4
1.1.1 Narrowband Internet of Things 4
1.1.2 Cellular Vehicle-to-Vehicle communications 4
1.2 Dissertation Organization 6
Chapter 2. Energy-saving Scheduling for 3GPP Narrowband Internet of Things (NB-IoT) Using Energy-aware Machine-to-Machine Relays 8
2.1 Introduction 8
2.2 Overview of NB-IoT Technology 11
2.2.1 NB-IoT Deployment 11
2.2.2 NB-IoT Scheduling 11
2.2.3 Proximity Services (ProSe) D2D/M2M (UE-to-Network) Relay 15
2.2.4 NB-IoT Studies 16
2.3 Problem Formulation and Solution 17
2.3.1 Problem Formulation 17
2.3.2 Solution 25
2.4 Simulation Results 30
2.5 Conclusion Remarks 40
Chapter 3. Adaptive Clustering and Scheduling for Dynamic Region-based Resource Allocation in V2V Communications 42
3.1 Introduction 42
3.2 Overview of C-V2V Communications 43
3.2.1 Sidlink for C-V2V Communications 43
3.2.2 Centralized or Distributed Scheduling Mode 44
3.2.3 Traffic Model for V2V Communications 45
3.3 Problem Formulation and Solution 47
3.3.1 Working Assumptions for the System Model 49
3.3.2 System Model 49
3.3.3 Problem Formulation 51
3.4 The Proposed ACSR Scheme 53
3.4.1 Phase 1 of the ACSR Scheme 55
3.4.2 Phase 2 of the ACSR Scheme 65
3.4.3 Implementation Consideration 69
3.5 Simulation Results 71
3.5.1 Evaluation Deployment 71
3.5.2 Performance Metrics 74
3.5.3 Performance of the ACSR Scheme 75
3.6 Conclusion Remarks 88
CHAPTER 4. CONCLUSION AND FUTURE WORKS 89
REFERENCE 90

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