8 research outputs found

    On erasure correction coding for streaming

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    We consider packet erasure correction coding for a streaming system where specific information needs to be decoded by specific deadlines, in order to ensure uninterrupted playback at the receiver. In our previous work [1], we gave a capacity-achieving code construction for the case of a fixed number of erasures. In this work, we consider a sliding window erasure pattern where the number of erasures within windows of size above some threshold is upper bounded by a fraction of the window size, modeling a constraint on burstiness of the channel. We lower bound the rates achievable by our previous code construction as a fraction of the capacity region, which approaches to one as the window size threshold and the initial playout delay increase simultaneously. © 2012 IEEE

    Streaming Codes for Channels with Burst and Isolated Erasures

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    We study low-delay error correction codes for streaming recovery over a class of packet-erasure channels that introduce both burst-erasures and isolated erasures. We propose a simple, yet effective class of codes whose parameters can be tuned to obtain a tradeoff between the capability to correct burst and isolated erasures. Our construction generalizes previously proposed low-delay codes which are effective only against burst erasures. We establish an information theoretic upper bound on the capability of any code to simultaneously correct burst and isolated erasures and show that our proposed constructions meet the upper bound in some special cases. We discuss the operational significance of column-distance and column-span metrics and establish that the rate 1/2 codes discovered by Martinian and Sundberg [IT Trans.\, 2004] through a computer search indeed attain the optimal column-distance and column-span tradeoff. Numerical simulations over a Gilbert-Elliott channel model and a Fritchman model show significant performance gains over previously proposed low-delay codes and random linear codes for certain range of channel parameters

    Rate-Optimal Streaming Codes for Channels with Burst and Isolated Erasures

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    Recovery of data packets from packet erasures in a timely manner is critical for many streaming applications. An early paper by Martinian and Sundberg introduced a framework for streaming codes and designed rate-optimal codes that permit delay-constrained recovery from an erasure burst of length up to BB. A recent work by Badr et al. extended this result and introduced a sliding-window channel model C(N,B,W)\mathcal{C}(N,B,W). Under this model, in a sliding-window of width WW, one of the following erasure patterns are possible (i) a burst of length at most BB or (ii) at most NN (possibly non-contiguous) arbitrary erasures. Badr et al. obtained a rate upper bound for streaming codes that can recover with a time delay TT, from any erasure patterns permissible under the C(N,B,W)\mathcal{C}(N,B,W) model. However, constructions matching the bound were absent, except for a few parameter sets. In this paper, we present an explicit family of codes that achieves the rate upper bound for all feasible parameters NN, BB, WW and TT.Comment: shorter version submitted to ISIT 201

    On erasure correction coding for streaming

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    Abstract—We consider packet erasure correction coding for a streaming system where specific information needs to be decoded by specific deadlines, in order to ensure uninterrupted playback at the receiver. In our previous work [1], we gave a capacity-achieving code construction for the case of a fixed number of erasures. In this work, we consider a sliding window erasure pattern where the number of erasures within windows of size above some threshold is upper bounded by a fraction of the window size, modeling a constraint on burstiness of the channel. We lower bound the rates achievable by our previous code construction as a fraction of the capacity region, which approaches to one as the window size threshold and the initial playout delay increase simultaneously. I

    On erasure correction coding for streaming

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