Tracking Forecast Memories for Stochastic Decoding

This paper proposes Tracking Forecast Memories (TFMs) as a novel method for implementing re-randomization and de-correlation of stochastic bit streams in stochastic channel decoders. We show that TFMs are able to achieve decoding performance similar to that of the previous re-randomization methods in the literature (i.e., edge memories), but they exhibit much lower hardware complexity. We then present circuit topologies for analog implementation of TFMs.

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