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Record W1518888629 · doi:10.1109/mwscas.2002.1187191

Development of a post-detection equalization technique for multicarrier modulation/demodulation systems

2003· article· en· W1518888629 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPAPR reduction in OFDM
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsEqualization (audio)DemodulationEqualizerComputer scienceSynchronization (alternating current)Modulation (music)Channel (broadcasting)SIGNAL (programming language)Adaptive equalizerElectronic engineeringSignal-to-noise ratio (imaging)Filter bankFilter (signal processing)Matched filterNoise (video)Control theory (sociology)TelecommunicationsEngineeringArtificial intelligenceAcoustics

Abstract

fetched live from OpenAlex

This paper is concerned with the development of a post-detection equalization technique for filterbank-based multicarrier modulation/demodulation systems. This technique is based on the equalization of the channel fractional delay in each subchannel in time synchronization with the constituent decimator at the receiver end, achieved through the exploitation of a subset of the signal samples at the input of the decimator. The resulting equalization gives rise to a high signal-to-noise ratio while requiring a short equalizer length. Moreover, it permits a tradeoff between various equalization parameters, leading to high computational flexibility. The search for an optimal solution can be constrained to within the channel lower and upper group-delay bounds within each subchannel, significantly simplifying the equalizer training.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.838
Threshold uncertainty score0.405

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)0.0000.000

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 head0.020
GPT teacher head0.250
Teacher spread0.230 · 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

Quick stats

Citations2
Published2003
Admission routes1
Has abstractyes

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