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Record W2125733728 · doi:10.1109/vetecf.2008.234

Joint PAPR and PICR Design in OFDM Systems

2008· article· en· W2125733728 on OpenAlexaff
Kewei Yuan, Zhiwei Mao

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPAPR reduction in OFDM
Canadian institutionsLakehead University
Fundersnot available
KeywordsOrthogonal frequency-division multiplexingJoint (building)Bit error rateReduction (mathematics)Computer scienceInterference (communication)Electronic engineeringNonlinear systemPower (physics)AlgorithmEngineeringTelecommunicationsMathematicsDecoding methodsChannel (broadcasting)

Abstract

fetched live from OpenAlex

High peak-to-average power ratio (PAPR) of orthogonal frequency division multiplexing (OFDM) signals results in inefficient operations of nonlinear devices used in OFDM systems and high peak interference-to-carrier ratio (PICR) of received signals degrades bit-error rate (BER) performance of the system. Joint design problem for OFDM systems considering both PAPR and PICR is investigated in this paper. We formulate a joint constrained and a joint weighted PAPR-PICR reduction problems, so that both PAPR and PICR are reduced and the performance of the system is improved. Algorithms are also developed to solve the joint PAPR and PICR design problems. Simulation results are presented to demonstrate efficacy of the proposed algorithms in reducing PAPR and PICR.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.119
Threshold uncertainty score0.249

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 head0.046
GPT teacher head0.194
Teacher spread0.148 · 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 designSimulation or modeling
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

Citations1
Published2008
Admission routes1
Has abstractyes

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