We investigate the performance-complexity tradeoffs of Raptor codes over Gaussian channels. Two different implementations of the belief-propagation (BP) decoding algorithm are considered, which we respectively refer to as "message-reset decoding" and "incremental decoding". We show that incremental decoding offers great advantages over message-reset decoding in terms of this tradeoff
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Hu et al. (2007) studied this question.
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