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Tracking Forecast Memories for Stochastic Decoding

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Abstract

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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Notes

  1. It should noted that the amount of reduction of physical wires between PNs and VNs in stochastic decoding is similar to other bit-serial decoding approaches such as the bit-serial MSA. This reduction directly translates to a high logic utilization of the decoder. For example, an 86% per-area core logic utilization was reported in [7] using the bit-serial MSA. This logic utilization is much higher than the 50% logic utilization obtained in [6] using 4-bit SPA.

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Acknowledgements

We would like to acknowledge the Natural Sciences and Engineering Research Council of Canada (NSERC), the Canada Research Chairs (CRC), and the Fonds Québécois de la Recherche sur la Nature et les Technologies (FQRNT) for their financial support.

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Authors and Affiliations

  1. Department of Electrical and Computer Engineering, McGill University, 3480 University Street, Montreal, Quebec, H3A 2A7, Canada

    Saeed Sharifi Tehrani, Ali Naderi, Guy-Armand Kamendje, Shie Mannor & Warren J. Gross

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  1. Saeed Sharifi Tehrani
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  2. Ali Naderi
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  3. Guy-Armand Kamendje
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  4. Shie Mannor
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  5. Warren J. Gross
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Correspondence to Warren J. Gross.

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Sharifi Tehrani, S., Naderi, A., Kamendje, GA. et al. Tracking Forecast Memories for Stochastic Decoding. J Sign Process Syst 63, 117–127 (2011). https://doi.org/10.1007/s11265-009-0441-5

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  • DOI: https://doi.org/10.1007/s11265-009-0441-5

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