A Low-Complexity PTS-Based Radix FFT Method for PAPR Reduction in OFDM Systems
Bibliographic record
Abstract
A low-complexity partial transmit sequence (PTS) technique for reducing the peak-to-average power ratio (PAPR) of an orthogonal frequency division multiplexing (OFDM) signal is presented. Signals at the middle stages of an -point radix FFT using decimation in frequency (DIF) or decimation in time (DIT) are considered for PTS subblocking. We show that DIF has a lower multiplicative complexity than DIT for similar PAPR reduction. A higher radix based FFT achieves better PAPR reduction per stage with less multiplicative complexity compared with a lower radix FFT. We further reduce the computational complexity by proposing a new technique, called decomposition PTS (D-PTS) subblocking, where subblocks are assigned through different stages of the transform. This new technique reduces the multiplicative complexity, while providing PAPR reduction similar to other techniques such as original PTS (O-PTS). Moreover, it has lower additive complexity.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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) | 0.003 | 0.001 |
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".