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On NACK-Based rDWS Algorithm for Network Coded Broadcast

机译:网络编码广播的基于NACK的rDWS算法研究

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The Drop when seen (DWS) technique, an online network coding strategy is capable of making a broadcast transmission over erasure channels more robust. This throughput optimal strategy reduces the expected sender queue length. One major issue with the DWS technique is the high computational complexity. In this paper, we present a randomized version of the DWS technique (rDWS), where the unique strength of the DWS, which is the sender’s ability to drop a packet even before its decoding at receivers, is not compromised. Computational complexity of the algorithms is reduced with rDWS, but the encoding is not throughput optimal here. So, we perform a throughput efficiency analysis of it. Exact probabilistic analysis of innovativeness of a coefficient is found to be difficult. Hence, we carry out two individual analyses, maximum entropy analysis, average understanding analysis, and obtain a lower bound on the innovativeness probability of a coefficient. Based on these findings, innovativeness probability of a coded combination is analyzed. We evaluate the performance of our proposed scheme in terms of dropping and decoding statistics through simulation. Our analysis, supported by plots, reveals some interesting facts about innovativeness and shows that rDWS technique achieves near-optimal performance for a finite field of sufficient size.
机译:在线网络编码策略是一种“丢弃时可见”(DWS)技术,能够使擦除信道上的广播传输更加健壮。此吞吐量最佳策略可减少预期的发送方队列长度。 DWS技术的一个主要问题是高计算复杂性。在本文中,我们提出了DWS技术(rDWS)的随机版本,其中DWS的独特优势(即,即使在接收方解码之前,发送方丢弃数据包的能力)也不受损害。使用rDWS可以降低算法的计算复杂性,但是此处的编码并不是吞吐量最优的。因此,我们对其进行了吞吐效率分析。发现对系数的创新性进行精确的概率分析是困难的。因此,我们进行两个单独的分析,即最大熵分析,平均理解分析,并获得系数创新概率的下限。基于这些发现,分析了编码组合的创新可能性。我们通过模拟对统计数据进行丢弃和解码来评估我们提出的方案的性能。我们的分析得到了图表的支持,揭示了一些有关创新性的有趣事实,并表明rDWS技术对于足够大的有限域实现了近乎最佳的性能。

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