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研究生： 蔡明輝
Tsai, Ming-Hui
論文名稱： 適性存取控制以提升在行動網路下連線容量之研究
Study on Adaptive Admission Control to Increase Connection Capacity in Mobile Networks
指導教授： 黃悅民
Huang, Yueh-Min
學位類別： 博士
Doctor
系所名稱： 工學院 - 工程科學系
Department of Engineering Science
論文出版年： 2015
畢業學年度： 103
語文別： 英文
論文頁數： 53
中文關鍵詞： 存取控制 、資源管理 、系統容量 、模糊類神經網路 、全球互通微波網路
外文關鍵詞： Call Admission Control, Resource Management, Sytem Capacity, Fuzzy Neural Network, WiMAX
相關次數： 點閱：96  下載：3 
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    • 因為具有較大的涵蓋範圍、較高的傳輸速率、較強的服務品質保證以及較低廉的佈建成本，移動式全球互通微波網路(mobile WiMAX)儼然成為諸多無線寬頻網路中一種值得令人期待的科技。然而，在系統容量與使用者滿意度之間，它仍然存在著許多資源有效使用與管理的議題值得探討與克服，特別是當其運用在多媒體傳輸時，所須注意的嚴格傳輸延遲限制。因此，我們提出了兩種存取控制機制(call admission control)以有效增加系統容量：一種是考量已緩衝的影音儲量來適性存取控制，另一種則是採用模糊類神經網路的智慧型存取控制。在本論文中，這兩種機制，即便在頻寬不足的情況下，也都能允許新的連線請求，進而達到增加系統的可連線容量，並且兼顧其連線的服務品質。當然，適性存取控制與論文中所提出的排程機制共同合作，使得即時影音連線的品質保證具有可行性。另外，我們也利用彈性調變與編碼(adaptive modulation and coding, AMC)的方式，讓影音連線能夠克服因為環境或移動所導致網路傳輸品質不穩的情形。最後，為了評估所提出的存取控制機制之效能，透過觀察即時的同時連線數(concurrent stream connection number)、連線請求被退機率(connection blocking probability)與影音品質低落之連線比(proportion of poor performance)等檢測數據，來評估不同資源管理(包含存取控制與排程機制)策略所帶來的效益。

    Mobile WiMAX has revealed as one of the most hopeful broadband wireless access technologies due to their characteristics of large network coverage, high transmission rate, strong QoS assurance and inexpensive deployment cost. However, there are still some challenging issues to be addressed such as resource management for system capacity and user gratification. Therefore, we propose two admission control mechanisms in order to efficiently increase system capacity, especially for multimedia transmission which ordinarily requires strict delay constrains. One is adaptive admission control with consideration buffered real time stream and the other is fuzzy neural intelligent admission control. In this dissertation, both of the control mechanisms can admit incoming video stream connections requests even without sufficient bandwidth to meet the QoS requirement. Certainly, the proposed adaptive scheduler can collaborate with admission control mechanisms to make QoS provision feasible. Also, each real time video connection keeps its fluency of performance over dynamic wireless channel status by employing adaptive modulation and coding (AMC) scheme. Finally, we evaluate the concurrent stream connection number, connection blocking probability and proportion of poor performance under different resource management strategies.

    摘要 III Abstract IV Acknowledgement V List of Figures VIII List of Tables IX List of Acronyms X Chapter 1 Introduction 1 1.1 Research Objectives 3 1.2 Organization of the Dissertation 5 Chapter 2 Background and Related Works 6 2.1 Overview of Mobile WiMAX 6 2.2 Resource Management in Mobile WiMAX 8 2.3 Resource Management Using Learning Mechanism 11 Chapter 3 Resource Management to Increase Connection Capacity 13 3.1 Introduction 13 3.2 Resource Management Framework with Consideration of Feedback USB 14 3.3 Simulations 21 3.4 Summary 24 Chapter 4 Fuzzy Neural Intelligent Admission Control in WiMAX 26 4.1 Introduction 26 4.2 Intelligent Admission Control Utilizing FNN 27 4.3 Performance Analysis and Discussion 40 4.4 Summary 44 Chapter 5 Conclusion and Future Works 46 5.1 Conclusion 46 5.2 Future Works 46 References 48 List of Figures Figure 1 1: USB is dependent on buffer capacity, bit rate and link quality 2 Figure 1 2: Adaptive admission control diagram with adaptive scheduler 3 Figure 2 1: Mobile WiMAX TDD Frame Structure 8 Figure 3 1: Adaptive admission control with consideration of feedback USB 15 Figure 3 2: An example illustrating the USB progressing of a given connection 20 Figure 3 3: The progress of CCN with/without feedback USB scheme 22 Figure 3 4: Connection blocking probability under different loads 23 Figure 4 1: Adaptive admission control with intelligent mechanism 28 Figure 4 2: Intelligent admission control with adaptive scheduling 31 Figure 4 3: The architecture of USB demarcation using FNN 32 Figure 4 4: Five layers FNN scheme 34 Figure 4 5 State diagram of channel state indicator 41 Figure 4 6: Concurrent connection number under diverse traffic peak 42 Figure 4 7: Connection blocking probability under diverse traffic peak 43 Figure 4 8: Proportion of poor performance under diverse traffic peak 44 List of Tables Table 2 1: 802.16e QoS classes 7 Table 3 1: Connections priority list based on different USB state and CSI (AAC) 19 Table 4 1: Connections priority list based on different USB state and CSI (AAC-FNN) 30 Table 4 2: Fuzzy rule base 36 List of Acronyms AAC adaptive admission control AAC-FNN adaptive admission control with fuzzy neural network AMC adaptive modulation and coding APA adaptive power allocation ARQ automatic repeat/retransmision request BS base station CAC call admission control CBP connection blocking probability CCN concurrent connection number CSI channel state information DL down link DSA dynamic subcarrier allocation FEC forward error correction FLC fuzzy logic controller FNN fuzzy neural network FTT fast fourier transform FUSC full usage of sub channels JRRM joint radio resource management JSAP joint subcarrier and power allocation MPDU MAC packets data units OFDM orthogonal frequency division multiplexing OFDMA orthogonal frequency division multiple access PPP proportion of poor performance PUSC partial usage of sub channels QoS quality of service rtPS real time polling service SCA static channel assigment sd starvation degree sli system load indicator SS subscriber station st sufficientcy threshold UL up link USB user stream buffer WiMAX worldwide interoperability for microwave access

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