Bibliographic record
Abstract
This paper introduces a multi-wavelet packet modulation (MWPM) which is a multi-band multi-dimensional modulation scheme with a flexible dyadic time-frequency tiling. The proposed MWPM can be considered as a generalization of orthogonal frequency division multiplexing (OFDM) or wavelet packet multiplexing (WPM). Compared to OFDM, the bandwidth efficiency of MWPM is increased r times for the multi-wavelet packets with multiplicity of r. In addition, the effects of frequency-selective wireless channels and high peak to average power ratio (PAPR) in OFDM can be mitigated in the new scheme by properly designing the MWPM dyadic structure. The implementation based on r/spl times/r matrix filters for MWPM is also presented in which the fast Mallat algorithm is extended into the vector form. To demonstrate MWPM effectiveness in wireless communication systems, this paper investigates the performance of M-ary QAM signaling combined with MWPM in different sub-bands for the additive white Gaussian noise (AWGN) channel, the slow flat Rayleigh fading channel and the Nakagami-m fading channel. With its advantages, the MWPM is a potential candidate for adaptive implementations in time varying and time dispersive fading channels.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".