A network coded ARQ protocol for broadcast streaming over hybrid satellite systems
Bibliographic record
Abstract
Due to the high round trip delay in satellite systems, the retransmission of lost packets using conventional ARQ schemes is performed in a very rigid manner and after a very long time of the initial packet transmission. This results in a high average packet delay and packet drop rate in broadcast streaming applications. Moreover, conventional ARQ schemes are generally inefficient in broadcast scenarios. In this paper, we propose a network coded ARQ protocol that performs both proactive and reactive packet retransmissions in hybrid satellite systems. The proposed protocol employs a network coding approach to generate efficient proactive retransmission packets without the knowledge of lost packets. This not only allows the transmission of these coded retransmissions before the arrival of the initial packets to their destinations but also achieves more efficient packet recovery compared to conventional ARQ. Reactive retransmissions in response to packet acknowledgments are then employed if one or more packets are still lost. Simulation results show considerable gains for our proposed protocol over the selective repeat ARQ protocol in terms of average packet delay, packet drop rate and goodput.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".