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Record W2122123085 · doi:10.1109/pimrc.2007.4394570

Opportunistic Configurations of Pilot Tones for PAPR Reduction in OFDM Systems

2007· article· en· W2122123085 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 institutionsDalhousie University
Fundersnot available
KeywordsOrthogonal frequency-division multiplexingReduction (mathematics)Pilot signalComputer scienceInterference (communication)Channel (broadcasting)Electronic engineeringSIGNAL (programming language)Envelope (radar)Frame (networking)AlgorithmMathematicsTelecommunicationsEngineering

Abstract

fetched live from OpenAlex

This paper introduces a peak-to-average power ratio(PAPR) reduction methodology in orthogonal frequency division multiplexing (OFDM) systems by deploying pilot tones in PAPR optimized configurations. Conventionally, the pilot tones in OFDM are used for channel estimation and carrier tracking. In this paper, in addition to maintaining their conventional functions, pilot tones, i.e., their signaling points and positions, are carefully chosen to "balance" the envelope peaks in the OFDM frame. Specifically, two methods are proposed, where both the magnitude and the phase information of the pilot tones are modified to reduce the PAPR of the OFDM signal. In the first method, similar to conventional applications, the pilot tones occur at the deterministic, known to the receiver, subcarriers whereas in the second method, a relaxation in the position of pilot tones is allowed. The proposed schemes achieve significant reduction in the PAPR, as measured using the complementary cumulative distribution function (CCDF) of the OFDM signal, without affecting the data rate of the system.

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: Empirical · Consensus signal: none
Teacher disagreement score0.619
Threshold uncertainty score0.319

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 head0.278
Teacher spread0.232 · 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

Citations6
Published2007
Admission routes1
Has abstractyes

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