Triangular Constellations for Adaptive Modulation
Bibliographic record
Abstract
Adaptive modulation is widely employed to improve spectral efficiency. To date, square signal constellations have been used with adaptive modulation. In this paper, triangular constellations are considered for this purpose. Triangle quadrature amplitude modulation (TQAM) for both power-of-two and non-power-of-two modulation orders is examined. A technique for TQAM mapping is presented which is better than existing approaches. A new type of TQAM called semi-regular TQAM (S-TQAM) is introduced. Bit error rate expressions for TQAM are derived, and the detection complexity of S-TQAM is compared with that of regular TQAM (R-TQAM) and irregular TQAM (I-TQAM). The performance of S-TQAM over additive white Gaussian noise and Rayleigh fading channels is compared with that of R-TQAM and I-TQAM.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".