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Record W2148643981 · doi:10.1145/1013235.1013306

Low-power asynchronous viterbi decoder for wireless applications

2004· article· en· W2148643981 on OpenAlexafffund
Mohamed Kawokgy, C.A.T. Salama

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicLow-power high-performance VLSI design
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAsynchronous communicationViterbi decoderComputer scienceViterbi algorithmCMOSWirelessPower (physics)Decoding methodsReduction (mathematics)State (computer science)Embedded systemElectronic engineeringComputer networkTelecommunicationsEngineeringAlgorithm

Abstract

fetched live from OpenAlex

This paper describes the implementation of an asynchronous 64-state, 1/2-rate Viterbi decoder using an original architecture and design methodology. The decoder is intended for wireless communications applications, where bit rates over 100 Mb/s and minimum power consumption are sought. The choice of an asynchronous design was predicated by the power and speed advantages of such a methodology. Asynchronous designs are inherently data driven and are active only when doing useful work, enabling considerable savings in power and operating at the average speed of all components. The decoder, implemented in a 0.18 µm CMOS technology, occupies an area of 2 mm 2 and operates above 200 Mb/s while consuming 85 mW: a 55% power reduction when compared to state of the art synchronous design implemented in a 0.25 µm technology.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.884
Threshold uncertainty score0.795

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.005
GPT teacher head0.205
Teacher spread0.200 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations20
Published2004
Admission routes2
Has abstractyes

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