反饋丟失條件下的即時譯碼網(wǎng)絡編碼研究
發(fā)布時間：2018-10-30 08:42
【摘要】：網(wǎng)絡編碼可顯著提高無線網(wǎng)絡系統(tǒng)性能,但是傳統(tǒng)網(wǎng)絡編碼中的信宿節(jié)點需收到足夠多的編碼信息才能譯碼,不能實現(xiàn)實時譯碼。即時譯碼的網(wǎng)絡編碼技術(Instantly Decodable Network Coding,IDNC)通過選擇相應數(shù)據(jù)包進行編碼,確保信宿節(jié)點可實時譯碼,因此受到了當前學者的廣泛關注。當前IDNC的研究大多基于理想的無線鏈路,但是現(xiàn)實環(huán)境中無線鏈路由于受到衰落、干擾等因素的影響,傳輸數(shù)據(jù)不可避免會出現(xiàn)差錯。因此本論文將研究無線鏈路反饋丟失條件下的IDNC,主要做了如下幾方面工作:1、在反饋丟失條件下,建立一種將IDNC和隨機線性網(wǎng)絡編碼(Random Linear Network Coding,RLNC)相關聯(lián)的網(wǎng)絡編碼模型。依據(jù)建立的IDNC圖,提出最優(yōu)IDNC解決方案下子代的概念,在每個子代中應用RLNC編碼模型。研究表明,子代大小介于1和IDNCC之間時,系統(tǒng)性能介于IDNC和RLNC之間,且IDNC和RLNC只是該模型下具有特定子代大小的兩個極端例子。2、在反饋丟失的多組播網(wǎng)絡中,為了使IDNC的完成時延和譯碼時延最小化,提出一種最有可能狀態(tài)找尋(Most Likely State Searching,MLSS)策略。通過MLSS方法建立多組播條件下的IDNC圖,依據(jù)該模型得出平均完成時延和譯碼時延的表達式,采用最大權頂點找尋算法找出使兩者分別最小化的團。仿真結果表明,相比于其他文獻利用盲IDNC圖更新法找尋最優(yōu)編碼包的算法,MLSS方法可獲得更優(yōu)的系統(tǒng)性能。3、為了權衡IDNC的完成時延和譯碼時延兩種性能,提出一種多組播網(wǎng)絡反饋丟失下的均衡完成時延和譯碼時延(Balance between Completion Time and Decoding Delay with Feedback Loss,BCD-FL)方案。首先用隨機最短路徑(Stochastic Shortest Path,SSP)分析IDNC在廣播網(wǎng)絡中的完成時延和譯碼時延均衡問題,利用分析出的性能表達式得到多組播網(wǎng)絡下BCD-FL問題的SSP描述,從而在IDNC圖中采用BCD-FL算法找出最大團。研究表明,提出的BCD-FL方案可較好均衡完成時延和譯碼時延性能。
[Abstract]:Network coding can significantly improve the performance of wireless network systems, but the traditional network coding nodes need to receive enough coding information in order to decode, can not achieve real-time decoding. The real-time decoding network coding technology (Instantly Decodable Network Coding,IDNC) ensures that the host node can be decoded in real time by selecting the corresponding packets to encode, so it has been widely concerned by scholars. Most of the current research on IDNC is based on the ideal wireless link, but in the real environment, due to the influence of fading, interference and other factors, the transmission data will inevitably appear errors. Therefore, this paper will study the IDNC, under the condition of wireless link feedback loss as follows: 1. Under the condition of feedback loss, we establish a kind of IDNC and random linear network coding (Random Linear Network Coding,. RLNC) the associated network coding model. According to the established IDNC diagram, the concept of offspring under the optimal IDNC solution is proposed, and the RLNC coding model is applied in each generation. The results show that when the offspring size is between 1 and IDNCC, the system performance is between IDNC and RLNC, and IDNC and RLNC are only two extreme examples with specific offspring size in this model. In order to minimize the completion delay and decoding delay of IDNC, a most probable state finding (Most Likely State Searching,MLSS) strategy is proposed. The IDNC graph under the condition of multi-multicast is established by MLSS method. According to the model, the expressions of average completion delay and decoding delay are obtained, and the max-weight vertex finding algorithm is used to find out the clusters which minimize the two groups respectively. The simulation results show that compared with other algorithms using blind IDNC graph updating method to find the optimal coding packet, the MLSS method can achieve better system performance. 3. In order to balance the completion delay and decoding delay of IDNC, the proposed method can achieve better performance. This paper presents a scheme for equalizing completion delay and decoding delay (Balance between Completion Time and Decoding Delay with Feedback Loss,BCD-FL under feedback loss in multi-multicast networks. Firstly, the completion delay and decoding delay equalization problem of IDNC in broadcast network is analyzed by stochastic shortest path (Stochastic Shortest Path,SSP), and the SSP description of BCD-FL problem in multi-multicast network is obtained by using the performance expression. Thus, the BCD-FL algorithm is used to find out the largest cluster in the IDNC diagram. The results show that the proposed BCD-FL scheme can equalize the performance of delay and decoding delay.
【學位授予單位】：南京郵電大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TN92
本文編號：2299512
[Abstract]:Network coding can significantly improve the performance of wireless network systems, but the traditional network coding nodes need to receive enough coding information in order to decode, can not achieve real-time decoding. The real-time decoding network coding technology (Instantly Decodable Network Coding,IDNC) ensures that the host node can be decoded in real time by selecting the corresponding packets to encode, so it has been widely concerned by scholars. Most of the current research on IDNC is based on the ideal wireless link, but in the real environment, due to the influence of fading, interference and other factors, the transmission data will inevitably appear errors. Therefore, this paper will study the IDNC, under the condition of wireless link feedback loss as follows: 1. Under the condition of feedback loss, we establish a kind of IDNC and random linear network coding (Random Linear Network Coding,. RLNC) the associated network coding model. According to the established IDNC diagram, the concept of offspring under the optimal IDNC solution is proposed, and the RLNC coding model is applied in each generation. The results show that when the offspring size is between 1 and IDNCC, the system performance is between IDNC and RLNC, and IDNC and RLNC are only two extreme examples with specific offspring size in this model. In order to minimize the completion delay and decoding delay of IDNC, a most probable state finding (Most Likely State Searching,MLSS) strategy is proposed. The IDNC graph under the condition of multi-multicast is established by MLSS method. According to the model, the expressions of average completion delay and decoding delay are obtained, and the max-weight vertex finding algorithm is used to find out the clusters which minimize the two groups respectively. The simulation results show that compared with other algorithms using blind IDNC graph updating method to find the optimal coding packet, the MLSS method can achieve better system performance. 3. In order to balance the completion delay and decoding delay of IDNC, the proposed method can achieve better performance. This paper presents a scheme for equalizing completion delay and decoding delay (Balance between Completion Time and Decoding Delay with Feedback Loss,BCD-FL under feedback loss in multi-multicast networks. Firstly, the completion delay and decoding delay equalization problem of IDNC in broadcast network is analyzed by stochastic shortest path (Stochastic Shortest Path,SSP), and the SSP description of BCD-FL problem in multi-multicast network is obtained by using the performance expression. Thus, the BCD-FL algorithm is used to find out the largest cluster in the IDNC diagram. The results show that the proposed BCD-FL scheme can equalize the performance of delay and decoding delay.
【學位授予單位】：南京郵電大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TN92
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