Backward Compatible Low-Complexity Demapping Algorithms for Two-Dimensional Non-Uniform Constellations in ATSC 3.0
Why this work is in the frame
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Bibliographic record
Abstract
Non-uniform constellation (NUC) is an advanced technology in digital terrestrial television broadcasting (DTTB) systems to reduce the shapping gap of BICM capacity to Shannon theoretical limit and provide performance gain. Two-dimensional NUC (2D-NUC) is a kind of NUC providing more gain but bringing higher demapping complexity at the receiver, which hinders its application prospects, especially in power limited systems. This paper proposes three novel demapping algorithms with reduced complexity for low to medium code rate 2D-NUCs in Advanced Television Systems Committee 3rd Generation (ATSC 3.0) standard. The proposed algorithms are based on the introduction of virtual points, the strategy of condensed symbols reduction and some reasonable approximations. There is a trade-off between the demapping complexity and performance. These three algorithms have different degrees of reduction in complexity and performance degradation, so they accommodate for different practical requirements. Theoretical analysis and simulation results are also given in this paper to prove the efficiency of the proposed demapping algorithms with reduced complexity.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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