本論文考慮一種運作在感知無線電環境下的車載網路（cognitive vehicular network）的應用問題：在受限於處在不同地理位置的車輛有不同的可供傳輸或接收頻帶條件下，正確收到gateway資料的車輛該如何選擇適當的通道同時轉播資料給鄰近未正確收到資料的車輛，以避免發生co-channel interference。我們稱此一問題為interference-free multi-channel poly-matching（簡寫成IMP）problem。此一問題的目標是使讓最多未正確收到資料的車輛也能獲得gateway的資訊。
本論文的主要貢獻有三：(1) 我們首先將此一IMP問題建模為semi-bipartite graph，並透過mathematical programming的方式來具體描述我們的問題與目標。(2) 我們提出集中式貪婪演算法有效率地解決此一問題。(3) 我們將集中式貪婪演算法轉換為一個新的分散式媒介存取控制協定，稱之opportunistic cooperative MAC（簡稱OC-MAC），使得每一個正確收到資料的車輛只需和鄰近的車輛交換訊息，便足以解決IMP問題，並使得未正確收到資料的車輛也能獲得gateway的資訊。
模擬實驗結果顯示，OC-MAC的效能（total throughput）和集中式貪婪演算法差不多，並且大幅勝過Random MAC。

In this thesis, we can consider an application scenario in cognitive vehicular networks: Under the condition that different vehicles in different locations may have different set of available licensed channels, how do the vehicles (called potential relays) that correctly received data from the gateway choose the proper channel to concurrently relay the data to the vehicles (called potential destinations) that did not receive data from the gateway such that the network throughput can be maximized. We call this problem the IMP (interference-free multi-channel poly-matching) problem. To the best of our knowledge, our thesis is the first one that seriously addresses and studies this issue.
The contributions of this thesis are mainly three-fold: (1) We use semi-bipartite graph and mathematical programming to formally model the IMP problem. (2) We design a centralized greedy algorithm to efficiently and effectively solve this problem. (3) On the basis of centralized greedy algorithm , we design a novel distributed medium access control protocol, named opportunistic cooperative MAC (OC-MAC for short), such that only via local information exchange between vehicles, the number of potential destinations that finally receive data from potential relays can be maximized.
Simulation results demonstrated that the throughput of OC-MAC is approximately equal to that of centralized greedy algorithm and is far superior to that of Random MAC.

論文審定書 i
誌謝 ii
摘要 iii
Abstract iv
目錄 v
圖次 vii
表次 ix
第一章 緒論 1
1.1 動機與目標 2
1.2 挑戰 3
1.3 貢獻 5
第二章 相關文獻 6
2.1 車載網路上的合作式通訊協定 6
2.2 感知無線網路上的通道存取控制協定 8
2.3 感知車載網路上的通道存取控制協定 9
第三章 OC-MAC協定 11
3.1 通道模型與SNR計算 11
3.2 網路模型 12
3.3 集中式貪婪演算法 16
3.3.1 基本概念 16
3.3.2演算法細則 17
3.3.3 貪婪演算法的範例 20
3.4 分散式OC-MAC協定 27
3.4.1 閘道廣播期 27
3.4.2 頻道偵測及資訊交換期 28
3.4.3 轉播端選擇期 32
3.4.4 資料轉送期 34
第四章 模擬實驗結果 35
4.1 實驗環境及參數設定 35
4.2 模擬器設計與實作 39
4.3 模擬實驗結果 40
4.3.1 Run-time Throughput 42
4.3.2 Primary user數量對效能的影響 43
4.3.3 Licensed channel數量對效能的影響 46
4.3.4 車子數量對效能的影響 49
4.3.5 車輛速度對效能的影響 52
4.3.6 RI封包廣播的成功率 55
第五章 結論 57
參考文獻 58

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