Abstract
BATS codes are a class of efficient random linear network codes. In this letter, BATS codes are generalized to incorporate batches of different sizes, and the corresponding belief propagation (BP) decoding performance is studied. Using a tree-based analysis, a sufficient condition is obtained such that the BP decoder can recover a given fraction of the input symbols with high probability. Some assumptions in the previous works are relaxed in our analysis so that the analytical results can be applied to more general scenarios.
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