Peak-to-average power ratio and intersymbol interference reduction by nyquist pulse optimization
Bibliographic record
Abstract
The efficiency of a power amplifier is partly determined by the peak-to-average power ratio (PAPR) of the modulated signal. Communication systems using high order QAM have large PAPR resulting in low efficiency and a high level of intermodulation distortion. In this paper, we propose a simultaneous minimization of the PAPR of the transmitted signal and the intersymbol interference (ISI) of the demodulated signal based on the optimization of the root raised cosine (RRC) filter. This is performed under spectral requirement constraints using a multivariate optimization technique. It is shown that the use of the proposed filters significantly increases the power amplifier efficiency while preserving the symbol error rate (SER) performance; 1.85 dB of power increase is typically obtained. Alternatively, they may be used to lower the spectral emissions and improve the error probability. The results were measured on a radio to obtain a 7 to 11 dB out of band signal power reduction.
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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) | 0.000 | 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".