隨著無線網路系統的快速發展，高頻寬的無線網路系統也隨之普及，相關的網路服務也快速發展。但無線網路系統本身容易受到環境與天候影響。當無線網路的傳輸通道受到外在的影響而造成訊號衰弱或干擾時，就會造成傳輸的封包遺失或錯誤。當影響過大時，對於偏重於即時性的相關網路服務造成相當大的影響，而其中又以影像串流服務影響最深。現有的影像串流編碼格式大多採用H.264/ MPEG-4 AVC，因為此編瑪格式除了本身的視訊編碼層外還額外加入了網路提取層，使得此編碼格式易於運用於各種傳輸環境。然而H.264/ MPEG-4 AVC影像編碼技術是藉由參考前後影像畫面，以提高影像的壓縮率與降低傳輸時所消耗的頻寬。因此當有一畫面遺失時，可能連帶接下來數個畫面解碼不完全或解碼失敗。
當封包遺失或錯誤時，傳統的做法是將該封包重新傳送，但此方法對於即時性的網路服務卻不適用。重傳的資料到達時，或許已超過需要他的時間點。因此在許多的研究上，如何保護封包又能運用於即時性的網路服務是一致力解決的問題。其中又以正向錯誤修正機制最能針對即時性的網路服務做封包保護。正向錯誤修正機制的原理是將冗餘的資訊加在原始的封包資料之後。當有封包遺失或錯誤時，利用此冗餘的資料來對遺失的資料進行修復或隱藏。然而原始的正向錯誤修正機制，無法因應網路環境做自適應的調整，而造成無法達到其最好的成效。
影像資料傳輸時，封包的大小不僅僅是影響到封包的數量與延遲時間，更會影響到影像的品質。在同樣的封包掉落率環境下，小封包傳輸的影像品質相較於大封包傳輸的影像品質會較差，因為小封包的傳輸勢必封包數量較多，有較高的機率影響到較多不同的畫面，而造成更多畫面無法解碼或解碼不完全。
於本研究中，我們將對使用里德-所羅門碼的正向錯誤修正機制進行優化，使其能依照現有網路環境狀態，而提供較有效的block大小與封包大小。由於在正向錯誤修正機制保護下的封包，因加入了修復的機制，不像純粹影像傳輸封包越大影像品質越好，並且在不同的block大小下時，因資料量的不同也會造成最佳的封包大小不同。另一方面，為了將使用正向錯誤修正機制進行封包保護的影像串流服務能運用於更多不同的硬體設備上，額外考量盡可能的選擇較小的block大小，以降低對硬體的要求與負擔。

As the Internet grows, Wireless Fidelity (Wi-Fi) has become more and more popular after the upgrades of transmission rate and transmission volume, which is attracting more network researchers in the study of high-quality video transmission. Meanwhile, more Internet users choose to connect to Internet services with mobile devices, like Tablets PCs and Smartphones. Of the many Internet services, video streaming is a frequently used Internet service. The appearance of MPEG-4 has made video streaming transmission become easier, which is the first video streaming protocol that includes network abstraction layer in it. The transmission of live streaming video has become better thanks to MPEG-4’s good network adaptability and its great fault tolerance on packet loses. However, there are still many unsolved problems such as packet loss and burst packet error.Forward Error Correction (FEC) is a common technology to protect data loss by redundant packets. Today there are various kinds of FEC to explore how to adaptively adjust the redundant packet amount and make adequate redundant packet overcome source error and loss. Both block size and packet size would affect the screening rate of source error and loss. When block size is small then the screening rate, it would be better than the case that block size is large; The impact on the quality of video streaming is greater when smaller packets are used. 
In this paper, we study the packet loss impact on the transmission quality of MPEG transmission with FEC in wireless networks. We are not only to consider the impacts in distributed packet loss, but also to study the impact in burst packet loss, which would affect the video transmission quality. Finally, we propose a new scheme called “Dynamically Adjust Block Size and Block Size (DABSPS)”. DABSPS adjusted the transmission packet size according to the wireless network environment, which reduced the impact on video quality and FEC packet screening error rate.

目錄
第一章 緒論	1
1.1	前言	1
1.2	動機與目的	2
1.3	論文章節架構	4
第二章 相關研究與背景資料	5
2.1	H.264/ MPEG-4 AVC 與其適應性編碼技術	5
2.2	H.264/ MPEG-4 AVC視訊壓縮標準	7
2.2.1	H.264/ MPEG-4 AVC的基本架構	7
2.2.2	三種不同類別特性的profile	12
2.3	H.264/ MPEG-4 AVC之適應性編碼技術簡介	20
2.4	H.264/MPEG-4 AVC之適應性編碼技術架構	21
2.5	H.264/MPEG-4 AVC適應性編碼之封包架構	23
第三章 改善封包遺失之技術	26
3.1	重傳機制	27
3.2	正向錯誤修正機制	28
3.3	交錯式順序機制	30
3.4	里德-所羅門碼	33
3.5	A Novel Multi-path Forward Error Correction	36
3.6	封包大小對影像串流的影響	37
第四章 正向錯誤修正機制較佳化	39
4.1	自適應調整Block 大小與封包大小	39
4.1.1	封包掉落範圍預測	42
4.1.2	調整較佳block大小與封包大小	44
第五章 模擬結果與效能分析	51
5.1	模擬環境	51
5.2	實驗模擬之結果與分析	53
第六章 結論與未來展望	61
參考文獻	63
圖目錄
圖2.1 VCL與NAL間的運作流程圖	9
圖2.2 編碼端VCL編碼過程	10
圖2.3 NAL header欄位定義[10]	11
圖2.4 各Profile技術支援比較表[12]	13
圖2.5  13個slice所組成的GOP編碼順序	16
圖2.6 錯誤擴散	17
圖2.7 時間性加權預測示意圖	19
圖2.8 H.264/AVC 之適應性編碼技術架構[14]	23
圖2.9 適應性編碼之網路提取層標頭	23
圖3.1 正向錯誤修正機制	29
圖3.2 交錯式順序矩陣	32
圖3.3 正向錯誤修正機制動作流程	35
圖3.4 不同的block大小之比較	36
圖3.5同掉落率下封包大小對影像的影響	38
圖4.1 自適應調整block與封包大小流程圖	41
圖5.1 GE 模組示意圖	52
圖5.2 模擬環境網路模型	53
圖5.3 基礎的FEC與理想化FEC	54
圖5.4 漸增的封包掉落率	56
圖5.5 凸波形封包掉落率	57
圖5.6 波浪形封包掉落率	57
圖5.7 波浪形封包掉落率	58
圖5.8 波浪形封包掉落率	59
圖5.9 波浪形封包掉落率	59
 
表目錄
表4.1 block大小為6	45
表4.2 block大小為7	45
表4.3 block大小為8	46
表4.4 block大小為9	46
表4.5 block大小為10	47
表4.6 block大小為11	47
表4.7 block大小為12	48
表4.8 block大小為13	48
表4.9 預測掉落率0.02至0.04之間的BVR值	50
表5.1於圖5.4中的各時間點封包掉落率	56
表5.2 於圖5.5中的各時間點封包掉落率	57
表5.3 於圖5.6中的各時間點封包掉落率	58
 

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