Layered-Division-Multiplexing for High Spectrum Efficiency and Service Flexibility in Next Generation ATSC 3.0 Broadcast System
Bibliographic record
Abstract
LDM, a non-orthogonal multiplexing technology, is one of the main innovations in ATSC 3.0, a next generation terrestrial TV broadcast system. This article gives a general overview of the LDM technology, its current applications in the ATSC 3.0 system, and its cost in terms of the required additional complexity. The transmission capacity benefit offered by LDM is explained by theoretical analysis and demonstrated by simulation results. An efficient implementation scheme is described with less than 15 percent complexity increase. New service coverage paradigms enabled by LDM are presented. Finally, more future innovative applications of LDM, along with their benefits and challenges, are introduced. These include using LDM for wireless in-band backhaul, combining LDM with scalable video coding, and the application of LDM in other future broadcasting and 4G/5G broadband systems.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".