臺灣博碩士論文加值系統

行動通訊網路的快速發展，從2G、3G、4G，以及目前正在發展中的5G網路，使得智慧裝置（smart devices）大量的增加。智慧裝置像是穿戴式裝置（wearable devices）的電池壽命有限，所以NB-IoT協定適用於穿戴式裝置來傳輸小資料（small data）以節省電量消耗。目前，穿戴式裝置亦能透過VoLTE用來進行通話。因此，NB-IoT以及LTE的共存網路在未來為必然的趨勢。然而UE若同時將兩種網路介面同時開啟，會造成耗電問題，因此我們設計協定切換節能省電機制（Protocol to Protocol Switching Mechanism），讓UE能夠被支援在NB-IoT以及LTE的共存網路環境之下，並且得以節省電力。在這篇論文當中，我們提供數學模型與建置模擬實驗來驗證我們提出的機制之效能。研究顯示我們的機制得以有效減少UE的耗電量。

The well development of Mobile Communications Networks (MCNs) causes the dramatically increasing of the smart devices. The smart devices such as wearable devices have limited battery lifetime so that it has the better choice to use the NB-IoT protocol to transmit the small data for the purpose of power saving. The wearable devices are also able to make the voice call through the VoLTE. Therefore, the interworking of the NB-IoT and LTE networks is necessary in the future. The power saving issue is generated if both NB-IoT and LTE interface of the UE attach to the networks. We propose the Protocol to Protocol Switching Mechanism (P2PSM) to enable the dual-mode UE to be supported in the NB-IoT and LTE interworking network and reduce the power consumption. The analytical models and simulation experiments are conducted to investigate the performance of the P2PSM mechanism. Our study shows that the proposed P2PSM mechanism can efficiently reduce the power consumption of the UE.

口試委員會審定書 #
誌謝 i
中文摘要 ii
ABSTRACT iii
CONTENTS iv
LIST OF FIGURES vi
LIST OF TABLES vii
Chapter 1 Introduction 1
Chapter 2 Protocol to Protocol Switching Mechanism (P2PSM) and Assistant-Wake-Up (AWU) Mechanism 5
2.1 The Protocol to Protocol Switching Mechanism 5
2.2 The Assistant-Wake-Up (AWU) Mechanism 9
2.2.1 Application Layer approach 9
2.2.2 Core Network Approach 10
Chapter 3 Analytical Model for P2PSM 12
3.1 Power Saving Ratio P_S 14
3.1.1 The probability that the UEN stays in the PTW (P_r) 14
3.1.2 The average power consumption with applying P2PSM (P_M) 17
3.1.3 The average power consumption without applying P2PSM (P_L) 26
3.2 Call Blocking Rate P_b 28
Chapter 4 Simulation Validation and Performance Evaluation 29
4.1 Simulation Validation 29
4.2 Performance Evaluation 30
4.2.1 Effects of User Behavior ¬¬E[t_a] and¬ ¬E[t_p] 31
4.2.2 Effects of Variance σ^2 34
4.2.3 Effects of The Assistant-Wake-Up (AWU) Mechanism 38
Chapter 5 Conclusion 39
APPENDIX 40
REFERENCE 42

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