臺灣博碩士論文加值系統

在本論文中，提出蜂巢式網路之分散型動態頻道配置最佳化的方法，並提供一套完整的動態頻道管理、選擇與重新配置，且考慮三種電磁相容性限制(Electromagnetic Compatibility，EMC)，分別為1.共同頻道限制(Co-Channel Constraint，CCC)、2.相鄰頻道限制(Adjacent Channel Constraint，ACC)、3.共同兩側限制(Co-Site Constraint，CSC)。本論文總共分為五部份，第一部份，介紹蜂巢式網路系統，接著提出研究動機，相關研究方法與論文架構說明。第二部份，說明電磁相容性限制，以及換手機制與何謂頻道重新配置。第三部份，針對方法做完整的介紹，像是頻道狀態、頻道狀態規定、頻道狀態表、頻道選擇策略與頻道重新配置策略。第四部份，說明模擬環境，接著介紹適應函數(Fitness Function)與基因演算法(Genetic Algorithms)執行步驟，並詳細描述基因演算法對於鎖定頻道配置與基因演算法對於交換頻道配置之方法。之後，將所提之方法與GALC、GASC做一完整比較，並且探討New Call以及Hand-off Call之阻塞率以及網路中可用通道數。最後，第五部份，將所提之方法做個總結，並由模擬結果可知，所提之方法能有效的改善蜂巢式網路之效能。

In this dissertation, we propose a method of the Optimization for Distributed Dynamic Channel Assignment of Cellular Network. Simultaneously, we also propose a complete dynamic channel management, selection and reassignment with the consideration of three type of Electromagnetic Compatibility (EMC), 1.Co-Channel (CCC), 2.Adjacent Channel Constraint (ACC), 3.Co-Site Constraint (CSC), respectively. This dissertation consists of five parts, the first part is the introduction of cellular network, then we propose our motivation, related works and structure statement of the dissertation. The second part is to describe EMC, Hand-off process and channel reassignment. The Third part, we introduce channel state, channel state rule, channel state table, channel selection and reassignment. The fourth part, we’ll introduce the execute step of simulation environment, fitness function and Genetic Algorithms, and describe the method of GALC and GASC. Then, we compare GALC with GASC and discuss available channel based, channel selection and channel reassignment schemes, blocking rate of new call and hand-off call. Finally, in conclusion, we could know our method can improve the performance of cellular network effectively through the simulation result.

索引目錄
中文摘要 I
Abstract II
致謝 III
索引目錄 IV
表目錄 VI
圖目錄 VII
第一章　緒論 1
1.1 蜂巢式網路系統 1
1.2 研究動機 3
1.3 相關研究方法與論文架構 4
第二章　蜂巢式網路環境 7
2.1 電磁相容性限制 8
2.2 換手機制 11
2.3 頻道重新配置 12
第三章　分散型動態頻道管理 14
3.1頻道狀態 14
3.2頻道狀態規定 19
3.3頻道狀態表 22
3.4頻道選擇策略 24
3.5頻道重新配置策略 41
第四章　模擬結果與比較 48
4.1 模擬環境 48
4.2比較方法 50
4.2.1基因演算法執行步驟 53
4.2.2 GALC執行步驟 56
4.2.3 GASC執行步驟 57
4.3模擬結果與比較 58
第五章　結論 66
參考文獻 67

表目錄
表3.3.1 考慮單位細胞25之頻道狀態表 24
表3.4.1 單位細胞28之頻道選擇考量 28
表3.4.2 單位細胞30之頻道選擇考量 32
表3.4.3 單位細胞36之頻道選擇考量 36
表3.4.4 單位細胞25之頻道選擇考量 39
表3.5.1 單位細胞24之頻道選擇考量 44

圖目錄
圖1.1. 蜂巢式網路架構 2
圖2. 1 ~ 49 Cell之編號 8
圖2.1.1單位細胞25使用了頻道K 9
圖2.1.2 第一層單位細胞 9
圖2.1.3 第二層單位細胞 10
圖2.1.4 第三層單位細胞 10
圖3.1.1 7*7 1 ~ 49 Cell之編號 15
圖3.1.2 三單位細胞叢集之同頻干擾範圍 15
圖3.1.3 單位細胞25配置K頻道動作前之狀態 16
圖3.1.4 單位細胞25配置K頻道動作後之狀態 17
圖3.1.5 七單位細胞叢集之同頻干擾範圍 17
圖3.1.6 單位細胞25配置K頻道動作前之狀態 18
圖3.1.7 單位細胞25配置K頻道動做後之狀態 19
圖3.2.1 頻道重複使用距離為三單位細胞 20
圖3.3.1 考慮單位細胞25之蜂巢式網路 23
圖3.4.1 1 ~ 49 Cell之編號 26
圖3.4.2 初始狀態可用頻道數量分佈圖 27
圖3.4.3 Call到達單位細胞28 28
圖3.4.4 配置單位細胞28後可用頻道數量分佈圖 29
圖3.4.5 頻道初始狀態配置圖 30
圖3.4.6 更新的頻道狀態圖 31
圖3.4.7 Call到達單位細胞30 32
圖3.4.8 配置單位細胞30後可用頻道數量分佈圖 33
圖3.4.9 更新的頻道狀態圖 34
圖3.4.10 Call到達單位細胞36 35
圖3.4.11 配置單位細胞36後可用頻道數分佈圖 36
圖3.4.12 更新的頻道狀態圖 37
圖3.4.13 Call到達單位細胞25 38
圖3.4.14 配置單位細胞25後可用頻道數量分佈圖 39
圖3.4.15 更新的頻道狀態圖 40
圖3.4.16 最後可用頻道數量分佈圖 41
圖3.5.1 頻道狀態I之狀態配置圖 42
圖3.5.2 頻道狀態J之狀態配置圖 43
圖3.5.3 單位細胞25之頻道1通訊結束 44
圖3.5.4 重新配置單位細胞24後可用頻道數量分佈圖 45
圖3.5.5 更新的頻道狀態圖 46
圖3.5.6 重新配置後可用頻道數量分佈圖 47
圖4.1.1 1 ~ 49 Cell之編號 49
圖4.1.2 Patterns#1平均Calls的到達率 49
圖4.1.3 Patterns#2平均Calls的到達率 50
圖4.2.1第三層單位細胞 51
圖4.2.2第三層含以外的單位細胞 52
圖4.2.2.1 GALC交換頻道配置 56
圖4.2.2.2 GALC Mutation操作與修補 57
圖4.2.3.1 GASC交換頻道配置 57
圖4.2.3.2 GASC Mutation操作與修補 58
圖4.3.1 Patterns#1只考慮New Calls比較其Blocked Rate 59
圖4.3.2 Patterns#2只考慮New Calls比較其Blocked Rate 59
圖4.3.3 Patterns#1使用DDCA不使用Reassignment機制 61
圖4.3.4 Patterns#2使用DDCA不使用Reassignment機制 61
圖4.3.5 比較Patterns#1 & Patterns#2之Blocked Rate 62
圖4.3.6 Patterns#1使用DDCA並使用Reassignment機制 63
圖4.3.7 Patterns#2使用DDCA並使用Reassignment機制 63
圖4.3.8 Patterns#1平均100通Calls之可用通道數 65
圖4.3.9 Patterns#2平均100通Calls之可用通道數 65

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