可变大小到达的流代码

Michael Rudow, K. V. Rashmi
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引用次数: 16

摘要

流码是一种卷积码,它对源数据包流进行编码,这些数据包在严格的解码延迟约束下顺序到达,以便在包擦除通道上传输。最近的一些工作已经提出了为包括突发和任意擦除的对抗性数据包擦除信道实现流代码结构的能力。据我们所知,流代码的现有模型考虑了一个设置,其中所有源数据包具有相同的固定大小。然而,实时视频流应用程序的源数据包具有高度可变的大小。在此应用的激励下,在本文中,我们提出了一个包含可变大小到达的流代码的广义模型。当信道不引入擦除时,源数据包大小的可变性在编码速率和最小解码延迟之间引起了新的权衡。我们还提出了一个用于可变大小到达的流代码的简单结构,它建立在为固定大小到达设计的现有流代码结构的基础上。当到达尺寸独立于具有有限支持的任何分布时,我们从理论上描述了所建议代码实现的速率。此外,使用实时视频跟踪和几个代表性参数设置,我们表明,与天真地使用为固定大小的到达设计的现有流代码相比,我们提出的代码构建实现了大约89.5%的上界速率,并且实现了显着更高的速率(10%-50%)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Streaming Codes For Variable-Size Arrivals
Streaming codes are a class of convolutional codes that encode a stream of source packets, which arrive sequentially with a strict decoding-delay constraint, for transmission over a packet-erasure channel. A number of recent works have proposed capacity achieving streaming code constructions for adversarial packet-erasure channels that include bursts and arbitrary erasures. The existing models for streaming codes, to the best of our knowledge, consider a setting where all the source packets are of the same, fixed size. However, live video streaming applications have source packets with highly variable sizes. Motivated by this application, in this paper, we present a generalized model for streaming codes that incorporates variable-size arrivals. The variability in the size of the source packets induces a new trade-off between the rate of the code and the minimum decoding delay when the channel introduces no erasures. We also present a simple construction of streaming codes for variable-size arrivals, which builds upon existing streaming code constructions designed for fixed-size arrivals. We theoretically characterize the rate achieved by the proposed code when arrival sizes are drawn independently from any distribution with a finite support. Furthermore, using a live video trace and several representative parameter settings, we show that proposed code construction achieves a rate of approximately 89.5% of an upper bound and achieves a significantly higher rate (10%-50%) than naively using the existing streaming codes designed for fixed-size arrivals.
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