MétaCan
Menu
Back to cohort
Record W2114630153 · doi:10.1109/lcomm.2009.12.091590

Power allocation for coded OFDM via linear programming

2009· article· en· W2114630153 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

VenueIEEE Communications Letters · 2009
Typearticle
Languageen
FieldEngineering
TopicPAPR reduction in OFDM
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsOrthogonal frequency-division multiplexingComputer scienceQuadrature amplitude modulationPhase-shift keyingModulation (music)Transmission (telecommunications)Convex optimizationAlgorithmBit error rateElectronic engineeringMathematical optimizationTelecommunicationsMathematicsDecoding methodsRegular polygonChannel (broadcasting)

Abstract

fetched live from OpenAlex

The combination of bit-interleaved coded modulation and orthogonal frequency-division multiplexing (BICOFDM) forms a powerful coded modulation scheme for transmission over wideband channels. Recently, Moon and Cox presented a new power allocation method to minimize the biterror rate (BER) of BIC-OFDM. It requires the solution of a convex optimization problem and is limited to (complex) binary transmission. Motivated by their work, in this letter we present an alternative power allocation method, which has the advantages of being a linear program and applicable to arbitrary signal constellations. Our approach relies on a BER approximation which becomes tight for asymptotically large signal-to-noise ratios. Simulative evidence shows that the proposed power allocation method achieves a performance very close to that from for the case of quadrature phase-shift keying.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.795
Threshold uncertainty score0.612

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 science0.0010.000
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 head0.025
GPT teacher head0.282
Teacher spread0.257 · 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