A low complexity selective mapping OFDM using multiple IFFT stages
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Bibliographic record
Abstract
A low complexity Selective Mapping (SLM) technique for reducing the Peak-to-Average Power Ratio (PAPR) of an Orthogonal Frequency Division Multiplexing (OFDM) signal is introduced. The intermediate signals within an N-point IFFT using a radix Decimation In Time (DIT) or Decimation In Frequency (DIF) IFFT algorithm are used to generate the phase sequences. It is shown that DIF provides lower multiplicative complexity in generating the SLM sequences compared to DIT, with the same PAPR reduction. In addition, a high radix FFT algorithm provides better PAPR reduction performance per stage with less multiplicative complexity compared to a low radix algorithm. We further reduce the computational complexity by proposing a low computational complexity technique based on multiplying the phase sequences at multiple IFFT stages. This new technique greatly reduces the multiplicative complexity while providing similar PAPR reduction to Ordinary SLM (O-SLM). The additive complexity is also reduced.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 it