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研究生: 張宗智
Chang, Jeng-Jr
論文名稱: 上行傳輸感知無線電系統中干擾減輕排程器之研究
Interference Mitigation Schedulers for the Uplink Cognitive Radios
指導教授: 張志文
Chang, Chih-Wen
學位類別: 碩士
Master
系所名稱: 電機資訊學院 - 電腦與通信工程研究所
Institute of Computer & Communication Engineering
論文出版年: 2009
畢業學年度: 97
語文別: 英文
論文頁數: 64
中文關鍵詞: 公平性排程功用函數干擾減輕排程感知無線電
外文關鍵詞: Cognitive radio, Scheduling, Interference mitigation, Scheduling utility function, Fairness
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  • 在重疊式(underlay)感知無線電系統下,有效率的利用頻譜資源和減輕對主要使用者之干擾是本論文兩個重要的目標。為了達到這兩個目標,我們提出干擾減輕排程器,此排程器主要藉由考慮感知使用者與主要使用者之間的通道衰減效應達到減輕干擾之作用。為此, 我們定義三個排程功用函數(scheduling utility function)以量化時變通道之影響。接著,在傳統排程器中加入排程功用函數後,我們提出以干擾減輕為基準之最大速率排程器(max-rate scheduler)、比例式公平排程器(proportional fair scheduler)、最大延遲排程器(max-delay scheduler)、改良式最大權重延遲優先排程器(modified largest weight delay first scheduler)。從模擬結果中發現,我們提出的干擾減輕排程器可以達到較高系統容量,同時有效的減少對主要使用者之干擾。另外,我們還有一些有趣的觀察,首先,環境參數即路徑衰減指數明顯影響排程功用函數之設計。第二,在一個嵌入主要使用者大細胞之集中式感知無線電系統中,加入適當的排程功用函數後,干擾減輕之最大速率排程器在公平性表現與比例式公平排程器一樣優異。這篇論文展現在重疊式感知無線電系統下,排程功用函數設計之重要性。我們相信,本論文結果可以提供系統設計者一些重要的建議。
    此外,我們也將上述之干擾減輕排程器應用於近年來逐漸興起的毫微微蜂巢式基地台(femtocell)系統;毫微微蜂巢式基地台是一種用來增進現存細胞網路系統的覆蓋率和傳輸率之技術。為了達到上述兩個目地,我們提出一個感知無線電毫微微蜂巢式基地台的概念,在此概念下,毫微微蜂巢式基地台具有偵測頻譜的能力。因此,我們引用干擾減輕概念設計該系統所需之排程器。另外,為了保護大細胞使用者,我們提出一個結合干擾減輕排程器與功率控制之策略。經由模擬結果,我們發現所提出的干擾減輕排程器在功率控制之感知無線電毫微微蜂巢式基地台中具有較低的中斷機率。

    The philosophies of this thesis are twofold: efficiently utilize the spectrum holes and mitigate the interference to the primary users for the uplink underlay cognitive radio (CR) systems. To achieve these two goals, we proposed the so-called interference mitigation-based (IM-based) schedulers by taking the effects of the fading channel between the CR and primary users into account. For this reason, three scheduling utility functions (SUF) are defined to characterize the impacts of time-varying fading channel. Then, the IM-based max-rate (MR), proportional fair (PF), max-delay (MD) and modified largest weight delay first (M-LWDF) schedulers are developed by incorporating the SUFs into the conventional schedulers. From the simulation results, we find that the proposed IM-based schedulers can achieve a higher capacity while efficiently reducing the interference to the primary users. Moreover, we also have some interesting observations. First, the environment parameters, e.g. the path-loss exponent, significantly affects the design of SUF. Second, in the centralized CR cell embedded in a large primary cell, the IM-based MR scheduler with a proper SUF can perform as well as PF schedulers in terms of the fairness index. This thesis reveals the importance of designing the SUFs for the underlay CR systems according to the environmental parameters. We also believe that the results of this thesis can provide some important hints for system designers.
    In addition, we also interest in a promising technique “femtocell”, which is proposed to improve both coverage area and data rate of existing cellular systems. To achieve these two goals, we proposed a concept of cognitive radio femtocell (CF), which means that the femtocell has ability to know radio scene around. Under this assumption, we take the concept of IM-based into account when designing schedulers for CF systems. Besides, a joint power control and IM-base schedulers strategy was proposed to protect macrocell user (MU). Through simulations, we find that the proposed IM-based schedulers with power control have lower outage probability than conventional schedulers in the cognitive radio femtocell system.

    Chinese Abstract i English Abstract iii Acknowledgements v Contents vi List of Tables ix List of Figures x Glossary of Symbols xiv 1 Introduction 1 1.1 Problem Formulation and Solution . . . . . . . . . . . . . . . . . . . . 1 1.1.1 Interference Mitigation-Based Schedulers for Cognitive Radios . 1 1.1.2 Interference Mitigation-Based Schedulers and Power Control for Cognitive Radio Femtocell Systems . . . . . . . . . . . . . . . . 4 1.2 Thesis Outline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 2 Background and Literature Survey 8 2.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 2.1.1 An Introduction to Cognitive Radios . . . . . . . . . . . . . . . 8 2.1.2 An Introduction to Femtocell . . . . . . . . . . . . . . . . . . . 9 2.1.3 Transmission Models for Cognitive Radios . . . . . . . . . . . . 11 2.2 Literature Survey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 2.2.1 Resource Allocation for Cognitive Radios . . . . . . . . . . . . . 12 2.2.2 Power Control for Cognitive Radios . . . . . . . . . . . . . . . . 13 3 Interference Mitigation-Based Schedulers for Cognitive Radios 14 3.1 System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 3.1.1 Interference Factor . . . . . . . . . . . . . . . . . . . . . . . . . 16 3.1.2 Scheduling Utility Function . . . . . . . . . . . . . . . . . . . . 16 3.2 Interference Mitigation-Based Schedulers . . . . . . . . . . . . . . . . . 17 3.2.1 The IM-Based MR Scheduler . . . . . . . . . . . . . . . . . . . 17 3.2.2 The IM-Based PF Scheduler . . . . . . . . . . . . . . . . . . . . 18 3.2.3 The IM-Based MD Scheduler . . . . . . . . . . . . . . . . . . . 19 3.2.4 The IM-Based M-LWDF Scheduler . . . . . . . . . . . . . . . . 21 3.3 Simulation Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 3.3.1 Simulation Model . . . . . . . . . . . . . . . . . . . . . . . . . . 22 3.3.2 Comparison of the Capacity and Interference . . . . . . . . . . . 24 3.3.3 The Effects of Path-Loss on the Capacity . . . . . . . . . . . . . 36 3.3.4 Comparison of the Fairness Index . . . . . . . . . . . . . . . . . 36 3.3.5 Comparison of the Delay . . . . . . . . . . . . . . . . . . . . . . 38 3.4 Chapter Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 4 Interference Mitigation-Based Schedulers and Power Control for Cognitive Radio Femtocell Systems 42 4.1 System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42 4.1.1 Interference Factor . . . . . . . . . . . . . . . . . . . . . . . . . 44 4.1.2 Scheduling Utility Function . . . . . . . . . . . . . . . . . . . . 44 4.2 Interference Mitigation-Based Schedulers . . . . . . . . . . . . . . . . . 45 4.2.1 The IM-Based MR Scheduler . . . . . . . . . . . . . . . . . . . 45 4.2.2 The IM-Based PF Scheduler . . . . . . . . . . . . . . . . . . . . 45 4.3 Joint Power Control and IM-Based Schedulers . . . . . . . . . . . . . . 46 4.3.1 Principle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 4.3.2 Power Control Mechanism . . . . . . . . . . . . . . . . . . . . . 48 4.4 Simulation Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 4.4.1 Simulation Model . . . . . . . . . . . . . . . . . . . . . . . . . . 49 4.4.2 Comparison of the Capacity and Interference . . . . . . . . . . . 51 4.4.3 Comparison of the Fairness Index . . . . . . . . . . . . . . . . . 53 4.4.4 Comparison of the Outage Probability . . . . . . . . . . . . . . 55 4.5 Chapter Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 5 Concluding Remarks 58 5.1 Interference Mitigation-Based Schedulers for Cognitive Radios . . . . . 58 5.2 Interference Mitigation-Based Schedulers and Power Control for Cognitive Radio Femtocell Systems . . . . . . . . . . . . . . . . . . . . . . . 59 5.3 Suggestions for Future Research . . . . . . . . . . . . . . . . . . . . . . 59 Bibliography 60 Vita 64

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