Tracking forecast memories for stochastic decoding

Saeed Sharifi Tehrani; Ali Naderi; Guy Armand Kamendje; Shie Mannor; Warren J. Gross

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

Tracking forecast memories for stochastic decoding

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

Research output: Contribution to journal › Article › peer-review

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.

Original language	English
Pages (from-to)	117-127
Number of pages	11
Journal	Journal of Signal Processing Systems
Volume	63
Issue number	1
DOIs	https://doi.org/10.1007/s11265-009-0441-5
State	Published - Apr 2011
Externally published	Yes

Keywords

ASIC
Iterative (channel) decoding
Low-density parity-check codes
Stochastic decoding

All Science Journal Classification (ASJC) codes

Control and Systems Engineering
Theoretical Computer Science
Signal Processing
Information Systems
Modelling and Simulation
Hardware and Architecture

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

Cite this

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title = "Tracking forecast memories for stochastic decoding",

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.",

keywords = "ASIC, Iterative (channel) decoding, Low-density parity-check codes, Stochastic decoding",

author = "{Sharifi Tehrani}, Saeed and Ali Naderi and Kamendje, {Guy Armand} and Shie Mannor and Gross, {Warren J.}",

note = "Funding Information: Acknowledgements We would like to acknowledge the Natural Sciences and Engineering Research Council of Canada (NSERC), the Canada Research Chairs (CRC), and the Fonds Qu{\'e}b{\'e}cois de la Recherche sur la Nature et les Technologies (FQRNT) for their financial support.",

year = "2011",

month = apr,

doi = "https://doi.org/10.1007/s11265-009-0441-5",

language = "الإنجليزيّة",

volume = "63",

pages = "117--127",

journal = "Journal of Signal Processing Systems",

issn = "1939-8018",

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T1 - Tracking forecast memories for stochastic decoding

AU - Sharifi Tehrani, Saeed

AU - Naderi, Ali

AU - Kamendje, Guy Armand

AU - Mannor, Shie

AU - Gross, Warren J.

N1 - Funding Information: 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.

PY - 2011/4

Y1 - 2011/4

N2 - 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.

AB - 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.

KW - ASIC

KW - Iterative (channel) decoding

KW - Low-density parity-check codes

KW - Stochastic decoding

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

M3 - مقالة

SN - 1939-8018

VL - 63

SP - 117

EP - 127

JO - Journal of Signal Processing Systems

JF - Journal of Signal Processing Systems

IS - 1

ER -

Tracking forecast memories for stochastic decoding

Abstract

Keywords

All Science Journal Classification (ASJC) codes

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