Coverage analysis on improved LTE eMBMS with layered-division-multiplexing and longer cyclic prefix
Bibliographic record
Abstract
3GPP is currently studying the improvement on the LTE eMBMS system to provide more capabilities and flexibilties on delivering multicast/broadcast services using the LTE infrastructure. This paper investigates the performance of an improved LTE eMBMS system using layered-division-multiplexing (LDM) technology and longer cyclic prefix (CP). The link-layer performance of using two-layer LDM in eMBMS system is first investigated with extensive computer simulations. Coverage analysis is then conducted on future eMBMS services with different cyclic prefix (CP) lengths, to allow more efficient deployment of multicast/broadcast single-frequency-network (MBSFN) for different cell sizes. The coverage performance is then used to demonstrate the capability of the improved eMBMS system with LDM to simultaneously deliver high-definition (HD) indoor/mobile services and ultra-HD fixed services targeting receivers with rooftop antennas.
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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 | 0.001 |
| 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 | 0.000 |
| 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".