Cooperative Coded Video Multicast for IPTV Services under EPON-WiMAX Integration
Bibliographic record
Abstract
This article introduces a novel framework of cooperative coded video multicast (CCVM) for provisioning IPTV services in metropolitan area access networks based on the emerging integration of Ethernet passive optical networks and WiMAX. The framework of CCVM is formed through the central coordination and synchronization at the optical line terminal and advanced coding techniques across different system layers. A cross-layer design of video multicasting on a single ONU-BS is first introduced for dealing with the multi-user channel diversity and short-term channel fluctuations, where the scalable video coding with multiple description coding (MDC) at the source and physical layer superposition coding techniques at the channel are jointly considered. This approach is further extended into the scenario that involves multiple ONU-BSs for cooperative communications to tackle intercell interference. Finally, the efficiency of the proposed framework is demonstrated via a case study on the employment of CCVM strategy under the collaboration of multiple distributed ONU-BSs.
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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 | 0.001 | 0.001 |
| 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 | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".