A new interpolation equalization scheme for discrete wavelet multitone modulation/demodulation systems
Bibliographic record
Abstract
Discrete Wavelet Multitone (DWMT) Modulation provides an alternative to the conventional Discrete Multitone (DMT) Modulation in various Digital Subscriber Line (xDSL) applications. The DWMT systems permit a high level of spectral containment and exhibit high robustness to narrowband noise and variations in channel frequency response characteristics. In this paper, an effective equalization scheme is presented for DWMT systems. Hitherto equalization schemes are based on pre- or post-detection equalization, optimization of the filterbank at the receiver, or combined optimization of filterbanks at the transmitter and receiver ends. In this paper, by taking into account the dominant effects of the non-integer channel delay, the pre- and post-detection equalization techniques are combined to obtain a novel interpolation equalization scheme. Simulation results show that the proposed technique results in a relative high Signal-to-Interference Ratio (SIR) and low computation complexity with one-tap interpolation equalization, leading to a high SIR close to the ideal channel case with multi-tap interpolation equalization.
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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 | 0.000 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".