傳統無線網路中的靜態頻譜配置方式是造成頻譜使用效率不彰的主要原因之一，為了改善這個現象，出現了一種新的網路型態，稱作感知無線網路(Cognitive Radio Network, CRN)，感知無線網路採用動態頻譜存取(Dynamic Spectrum Access, DSA)技術，讓網路傳輸得以在頻譜空洞(spectrum hole)間靈活的切換使用，藉此提升頻譜使用效率。本研究考量了在感知無線網路中，由於每個次要使用者(Secondary User, SU)因為所處位置以及周遭頻譜環境的不同，會有不同的可用頻道(available channel)，如何配置這些可用頻道將會是影響整個系統效能的關鍵。然而在既有機制中，並未考量到多路徑衰減(multipath fading)問題，因此，本研究提出一個改良的頻道配置機制，基於模糊理論，加入次要使用者所接收訊號強度的考量，透過模糊理論的計算，制定出次要使用者頻道存取的優先權。最終，模擬結果證明了所提機制的網路吞吐量(throughput)優於既有機制，驗證了所提機制之有效性。

In traditional wireless networks, fixed allocation of spectrum is one of the main reason causing low utilization of spectrum. In order to solve this problem, a new wireless communication model has been proposed, which called Cognitive Radio Networks (CRN). CRN adopts Dynamic Spectrum Access (DSA) technology, thus it can flexibly use the spectrum which primary user temporarily unused. In cognitive radio networks, due to each secondary user (SU) has different location and surrounding spectrum environment, it may have variety of available channels. How to assign these available channels is the crucial point of system performance. However, existing methods doesn’t consider the problem of multipath fading; therefore, this study proposed an improved channel allocation scheme. We consider the received signal strength to define the channel access priority of secondary users   applied by fuzzy theory. Finally, the simulation results show the superior of our approach and verify the effectiveness of the proposed scheme.

目錄
圖目錄	V
表目錄	VII
第一章 緒論	1
1-1 研究背景	2
1-2 研究動機	6
1-3 研究目的	7
1-4 論文架構	8
第二章 相關研究與背景介紹	9
2-1 感知無線網路中的頻道配置機制	10
2-1-1 具回饋的頻道配置機制	11
2-1-2 不具回饋的頻道配置機制	16
2-2 模糊理論	18
2-2-1 模糊化(Fuzzification)	20
2-2-2 模糊知識庫(Fuzzy Knowledge Base)	23
2-2-3 推論引擎(Inference Engine)	24
2-2-4 解模糊化(Defuzzification)	26
第三章 模糊動態頻道配置機制	27
3-1 網路環境設定	29
3-2 建立可用頻道表	32
3-2-1 能量偵測法(Energy Detection)	33
3-2-2 融合決策(Fusion Decision)	36
3-3 次要使用者優先權排程	38
3-3-1 次要使用者提出傳輸需求	40
3-3-2 依據歸屬函數執行模糊化	43
3-3-3 依據規則庫執行模糊推論	49
3-3-4 規則驗證及解模糊化	53
3-3-5 頻道配置	59
第四章 模擬比較與分析	60
4-1 模擬環境與參數設定	61
4-2 模擬結果與分析比較	64
第五章 結論與未來研究方向	68
5-1 結論	68
5-2 未來研究方向	69
參考文獻	70
附錄 - 英文論文	76

圖目錄
圖 1.1	Dynamic Spectrum Access (DSA)	3
圖 1.2	Cognitive Radio Network Architecture	5
圖 2.1	Cognitive cycle	10
圖 2.2	The signaling flows of Cognitive Relay	13
圖 2.3	System model for multi-band dynamic spectrum sharing	15
圖 2.4	Hierarchical system comprising two FLS	17
圖 2.5	Fuzzy Inference System	19
圖 2.6	Triangular membership function	21
圖 2.7	Trapezoidal membership function	22
圖 2.8	Linguistic Variable	23
圖 2.9	Mamdani’s min-min-max Inference	25
圖 3.1	Fuzzy-based dynamic channel allocation scheme	28
圖 3.2	System model	29
圖 3.3	Sequence diagram	30
圖 3.4	Time slots illustration	31
圖 3.5	Flow chart for establish the available channel table	32
圖 3.6	Energy Detection	33
圖 3.7	Hidden terminal problem	34
圖 3.8	Flow chart for SU priority scheduling	39
圖 3.9	Proposed Fuzzy Inference System with four input	40
圖 3.10	Membership function of Spectrum utilization Efficiency	44
圖 3.11	Membership function of Mobility	45
圖 3.12	Membership function of Distance	46
圖 3.13	Membership function of Signal Strength	47
圖 3.14	Membership function of Priority factor	48
圖 3.15	Priority factor with Signal Strength = -60dB and Distance = 350m	54
圖 3.16	Priority factor with Signal Strength = -60dB and Mobility = 15m/s	54
圖 3.17	Priority factor with Signal Strength = -60dB and Spectrum utilization Efficiency = 50%	55
圖 3.18	Priority factor with Distance=350m and Mobility = 15m/s	55
圖 3.19	Priority factor with Distance = 350m and Spectrum utilization Efficiency = 50 	56
圖 3.20	Priority factor with Spectrum utilization Efficiency = 50% and Mobility = 15m/s 	56
圖 3.21	Proposed Fuzzy Inference System paradigm	58
圖 4.1	Simulation environment	63
圖 4.2	Priority variation with different Signal Strength	65
圖 4.3	Case of three input (without Signal Strength)	66
圖 4.4	Analysis of average throughput per SU	66
圖 4.5	Analysis of total throughput of secondary network	67

表目錄
Table 1	Four possible scenarios for spectrum sensing	34
Table 2	Available channel table	37
Table 3	Rule Table	51
Table 4	Available channel table (update by Priority factor)	59

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