Pulse Shaping for Faster-than-Nyquist to Enable Low-Complexity Detection
Why this work is in the frame
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Bibliographic record
Abstract
In this paper, we consider the problem of designing pulse shaping for faster-than-Nyquist (FTN) signaling. The proposed pulse shape is based on the optimization constraint such that the resulting intersymbol interference (ISI) matrix possesses super increasing sequence criteria. The low-complexity symbol-by-symbol sequence estimator which relies on this specific criteria can perform reasonably well even for lower values of time packing <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\tau=0.6$</tex>. We formulate the problem as a finite impulse response (FIR) design and propose a second-order code program (SOCP) based solution. Simulation results show that with our proposed pulse shaping design for <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\tau=\{0.8,0.6,0.5\}$</tex>, we obtain 2 dB or more performance improvement at a bit-error-rate (BER) of 10<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">–3</sup>compared to the state-of-the-art existing detection schemes over an additive white Gaussian noise (AWGN) channel.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 it