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Record W2059510432 · doi:10.1049/ip-com:20040548

Quantiser design for AWGN and Rayleigh fading BPSK channels with soft output decoding

2004· article· en· W2059510432 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEE Proceedings - Communications · 2004
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Data Compression Techniques
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsAdditive white Gaussian noisePhase-shift keyingRayleigh fadingDemodulationDecoding methodsFadingAlgorithmMathematicsChannel (broadcasting)TelecommunicationsComputer scienceElectronic engineeringBit error rateEngineering

Abstract

fetched live from OpenAlex

A new method of combined source-channel coding for the scalar quantisation of a discrete memoryless source is presented that takes advantage of the channel soft output values produced by the demodulator. The case of transmitting a memoryless Gaussian source using binary phase shift keying (BPSK) modulation over over an additive white Gaussian noise (AWGN) channel with and without Rayleigh fading is studied. Numerical results using some closed form expressions are presented, showing up to 1 dB improvement in the end-to-end distortion with respect to a traditional channel optimised scalar quantiser.

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.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.439
Threshold uncertainty score0.825

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 studies0.0010.000
Scholarly communication0.0000.002
Open science0.0030.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.083
GPT teacher head0.317
Teacher spread0.234 · 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