PAPR Reduction in Wavelet Packet Modulation Using Tree Pruning
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.
Bibliographic record
Abstract
High peak-to-average power ratio (PAPR) of transmitted signals is a major drawback for multicarrier modulation systems such as orthogonal frequency division multiplexing (OFDM) and wavelet packet modulation (WPM). In this paper, wavelet packet tree pruning is proposed for the reduction of PAPR in WPM systems. In this technique, a full wavelet packet tree is dynamically pruned via joining and splitting of terminal nodes to achieve a minimized PAPR. Specifically, alternative mappings of data symbols onto different tree structures are generated, and the time domain sequence with the smallest PAPR is transmitted. The information about the pruned tree is sent as side information similar to techniques such as selective mapping (SLM) in OFDM systems. Using a small level of redundancy for side information, the proposed scheme achieves significant reduction in PAPR at the expense of acceptable computational complexity. The complementary cumulative distribution function (CCDF) of the PAPR optimized signal shows about a 3.5 dB improvement over the original WPM signal.
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 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