Abstract
Batched sparse (BATS) coding is a promising new technique designed for reliable transmissions over erasure networks, which can achieve asymptotic bandwidth optimality. However, the decoder of the conventional BATS codes begins to recover the source packets only after receiving a sufficient number of encoded packets which induces delay. Moreover, the larger the source block size is, the longer the time delay will be. In this paper, we propose a scheme by using expanding window applied over BATS codes, termed the expanding-window BATS codes, which divide the source data into smaller blocks for reducing delay. Furthermore, for improving the decoding performance we design an adaptive encoder which encodes the source packets with dynamic encoding probabilities. Because the performance of BATS codes highly depends on the degree distribution, we further optimize the degree distributions for the proposed expanding-window BATS codes with linear programming and the performances have been verified by the simulation results.
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