Opportunistic Configurations of Pilot Tones for PAPR Reduction in OFDM Systems
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".