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Record W2152302807 · doi:10.1109/glocom.2003.1258646

Power loading for CP-OFDM over frequency-selective fading channels

2004· article· en· W2152302807 on OpenAlexaff
Neng Wang, Steven D. Blostein

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Communication Techniques
Canadian institutionsQueen's University
Fundersnot available
KeywordsCyclic prefixFadingOrthogonal frequency-division multiplexingBit error rateTransmission (telecommunications)Computer scienceSignal-to-noise ratio (imaging)Block (permutation group theory)Power (physics)Electronic engineeringAlgorithmTelecommunicationsMathematicsChannel (broadcasting)EngineeringPhysics

Abstract

fetched live from OpenAlex

We compare cyclic prefix (CP) based single and multicarrier block transmission schemes in frequency-selective fading channels. Analytical comparison shows that at moderate-to-high signal-to-noise ratio (SNR), the uncoded error rate performance of multicarrier transmission is inferior to that of single carrier. We propose new minimum bit error rate (MBER) power loading algorithms for multicarrier transmission. It is also shown that a simpler approximate MBER (AMBER) power loading method has performance close to that of the optimum MBER scheme. Performance of a variety of methods is compared analytically and verified by simulations.

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: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.882
Threshold uncertainty score0.664

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 head0.013
GPT teacher head0.264
Teacher spread0.252 · 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
GenreMethods

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

Citations17
Published2004
Admission routes1
Has abstractyes

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