A Novel Adaptive FEC and Interleaving Architecture for H.264/SVC Wireless Video Transmission

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[[alternative]]A novel adaptive FEC and interleaving architecture for H.264/SVC wireless video transmission

碩士[[abstract]]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發展，但於無線的網路環境之中，網路的品質則深受環境與天候的影響。當無線網路的傳輸通道本身受到外界的影響而造成訊號衰減或干擾時，就會造成封包的遺失，因為這些因素所造成的封包遺失稱為無線遺失。當無線遺失情形嚴重時，對於偏重即時性之相關服務會是相當大的影響，如：影像串流服務便是其中之一。H.264/AVC影像編碼技術藉由參考前後之影像畫面，以提高影像的壓縮率與降低影像串流時所消耗的頻寬量。但因為此特性，當有一畫面遺失時就可能連帶影響前後數個畫面之品質與解壓縮。 傳統的錯誤回復機制對於即時回復錯誤的封包資訊的能力有限。在許多的研究上，都致力於解決這問題。例如，正向錯誤修正機制(FEC)與自動重傳請求協議(ARQ)。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，並利用此冗餘的資訊來回復錯誤或遺失的原始資訊。雖然正向錯誤修正機制比起自動重傳請求協議排除了時間上的延遲，但是卻使用了較多的頻寬資源。 因此近來，Enhanced Adaptive FEC (EAFEC)被提出，用以改善影像串流在無線網路上的傳輸效能。EAFEC基於網路流量與無線頻道的狀態，來動態決定冗餘資訊之長度，以減少不必要之冗餘資訊的傳輸，並達成更有效使用無線網路頻寬資源之目的。 於本研究中，我們將利用正向錯誤修正技術的特性，配合適應性編碼技術的層級式影像編碼架構與交錯式順序方法來延伸增強EAFEC機制之效能。此一新的機制，對於不同重要性的影像資訊能提供不同的保護強度。例如，較重要之資料給予較強之保護強度，以保證其資料的正確性；而重要程度相對低之資料則給予相對低之保護強度。此外我們提出之新機制也改善了以往遭遇連續性封包遺失時，資料的成功修復率。在此研究中，我們的主要目標是依據不同重要性的影像資料，結合網路流量和無線頻道的狀態。分別動態調整各個不同重要性資料的資料保護強度，以能更有效率的利用無線網路之頻寬資源。[[abstract]]The main challenge of wireless video transmission originates from the error-prone nature caused by the time-varying channel itself. By complex calculation of preceding and succeeding frames, the H.264 video compression standard achieves high compression ratios. Packet loss degrades its quality and even affects the decoding of dependent frames. This means that the error spreads to the neighboring frames as well which depend on the several preceding differentially coded frames. The unavoidable wireless video transmission errors make it hard for the traditional error recovery techniques to recover the lost video packets timely. Many studies have tried to solve this problem and their major design consideration has been given to the total throughput. Such studies include Forward Error Correction (FEC) and Automatic Retransmission ReQuest (ARQ). In FEC approach, the source node transmits the parity packets along with the original data packets. The receiver can accurately recover any lost data packets less than the parity packets. The amount of the parity packet is determined at the time of FEC encoding. Although eliminating the need for time-consuming acknowledgement and retransmission operations of ARQ, FEC consumes more bandwidth. Recently, an intelligent FEC mechanism, Enhanced Adaptive FEC (EAFEC), has been proposed to provide improved video delivery over wireless networks. Based on both network traffic load and wireless channel state, the redundant FEC packets are dynamically added. Instead of adding unnecessary packets into the congested network, EAFEC algorithm tunes FEC packet numbers in such a way. In this research, we extend the EAFEC scheme to further propose and analyze the effeciency of using different FEC strength depending on H.264/SVC video stream priorities for wireless video transmission. In this scheme, we define different threshold groups to compute the FEC strength (the number of redundant packets) for the specified H.264/SVC video stream priorities with the EAFEC scheme. To protect data from the burst loss between the Access Point (AP) and the client nodes, the interleaving technique for each H.264/SVC FEC video data is also introduced. The adaptive FEC strength to different priority video frame under current rate of wireless channel loss is the objective of this research.[[tableofcontents]]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 - 5 - 第二章 H.264/AVC與其適應性編碼技術 - 7 - 2.1 H.264視訊壓縮標準簡介 - 7 - 2.2 H.264/AVC視訊壓縮標準 - 9 - 2.2.1 H.264/AVC的基本架構 - 9 - 2.2.2 三種不同類別特性之profile - 13 - 2.3 H.264/AVC之適應性編碼技術簡介 - 22 - 2.4 H.264/AVC之適應性編碼技術架構 - 23 - 2.5 H.264/AVC適應性編碼之封包架構 - 26 - 2.6 JSVM軟體簡介 - 28 - 2.6.1 JSVM軟體的下載與重建 - 28 - 第三章 改善封包遺失之技術 - 30 - 3.1 重傳機制 - 31 - 3.2 正向錯誤修正機制 - 32 - 3.3 交錯式順序機制 - 35 - 第四章 提出新的層級式FEC結合架構 - 40 - 4.1 Enhanced Adaptive FEC介紹 - 43 - 4.1.1 Enhanced Adaptive FEC基本概念 - 43 - 4.1.2 Enhanced Adaptive FEC演算法 - 45 - 4.2 結合SVC特性之新的層級式FEC架構 - 47 - 4.2.1 層級式FEC架構演算法 - 49 - 4.3 新的層級式FEC與Interleaving之結合架構 - 55 - 4.3.1 層級式FEC與Interleaving之結合架構 - 56 - 第五章 模擬環境及模擬結果分析 - 59 - 5.1 模擬環境之架構 - 59 - 5.2 模擬環境之參數設定 - 61 - 5.2.1 網路環境參數設定 - 61 - 5.2.2 影像串流參數設定 - 62 - 5.3 實驗模擬之結果與分析 - 65 - 第六章 結論與未來展望 - 78 - 參考文獻 - 80 - 圖目錄 圖2.1 VCL和NAL間的運作流程圖 - 10 - 圖2.2 Encode端VCL編碼過程 - 11 - 圖2.3 NAL header欄位定義 - 12 - 圖2.4 各Profile內部技術支援比較表 - 15 - 圖2.5 以13個Slice組成之GOP編碼順序 - 18 - 圖2.6 時間性加權預測示意圖 - 21 - 圖2.7 H.264/AVC之適應性編碼技術架構 - 25 - 圖2.8 適應性編碼之網路提取層標頭 - 26 - 圖3.1 正向錯誤修正機制 - 33 - 圖3.2 3*3交錯式順序矩陣 - 37 - 圖3.3 交錯式順序發生連續封包遺失的情況 - 38 - 圖4.1 新的層級式FEC結合架構 - 42 - 圖4.2 經由Wireless AP執行FEC運算架構圖 - 44 - 圖4.3 EAFEC pseudocode - 45 - 圖4.4 EAFEC演算法之FEC冗餘封包數目運算流程 - 47 - 圖4.5 4×4交錯式順序矩陣 - 57 - 圖5.1 模擬網路架構圖 - 60 - 圖5.2 H.264 SVC影片之階層式預測架構 - 63 - 圖5.3 不同影像層級的封包遺失率 - 66 - 圖5.4 不同FEC機制的封包遺失 - 67 - 圖5.5 不同影像層級的封包遺失率比較 - 68 - 圖5.6 不同FEC機制的封包遺失狀況 - 69 - 圖5.7 不同FEC機制的冗餘封包數量 - 70 - 圖5.8 不同影像層級的封包遺失率 - 72 - 圖5.9 各個FEC機制的封包遺失比較 - 73 - 圖5.10 影像基本層封包遺失率的比較 - 74 - 圖5.11 不同FEC機制的冗餘封包數量比較 - 76 - 表目錄 表2.1 CVS存取參數 - 29 - 表4.1 EAFEC演算法符號表 - 46 - 表4.2 SVC影像串流資料重要性程度的分類 - 50 - 表5.1 網路系統環境參數 - 61 - 表5.2 H.264 SVC影片參數 - 63 -[[note]]學號: 696450013, 學年度: 9

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