Low Field-size, Rate-Optimal Streaming Codes for Channels With Burst and Random Erasures
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In this paper, we design erasure-correcting codes for channels with burst and random erasures, when a strict decoding delay constraint is in place. We consider the sliding-window-based packet erasure model proposed by Badr et al., where any time-window of width w contains either up to a random erasures or an erasure burst of length at most b. One needs to recover any erased packet, where erasures are as per the channel model, with a strict decoding delay deadline of τ time slots. Presently existing rate-optimal constructions in the literature require, in general, a field-size which grows exponential in τ, for a constant a/τ. In this work, we present a new rate-optimal code construction covering all channel and delay parameters, which requires an O(τ^2) field-size. As a special case, when (b-a)=1, we have a field-size linear in τ. We also present three other constructions having linear field-size, under certain constraints on channel and decoding delay parameters. As a corollary, we obtain low field-size, rate-optimal convolutional codes for any given column distance and column span. Simulations indicate that the newly proposed streaming code constructions offer lower packet-loss probabilities compared to existing schemes, for selected instances of Gilbert-Elliott and Fritchman channels.
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