Joint control of delay and packet drop rate in satellite systems using network coding
Bibliographic record
Abstract
Mobile terminals communicating through satellite suffer from low channel quality due to the combination of slow and fast fading and limited battery power. Moreover, the advanced applications proliferating over such terminals forbids the use of feedback based packet retransmission schemes over satellite due to their high latency, exceeding three times the round trip time. These feedback based packet retransmission schemes also suffer from large throughput degradations to reduce packet drop rates, especially for the large receiver population. In this paper, we propose a joint delay and packet drop rate control protocol over lossy mobile satellite channels using network coding. The suggested protocol employs random network coding at the mobile terminals, within and across different sessions, to generate efficient proactive retransmission packets, without prior knowledge of lost packets at the different users. It also allows the satellite to transmit random network coding combinations of all received packets, to fill the gaps left by packet losses on the uplink channel. By adjusting the timing of these network coded transmissions, the protocol can control packet recovery at any desired delay above one round trip time. The protocol can also control the packet drop rate level by adjusting the network coding rate. The protocol is able to achieve these gains at a much higher system throughput compared to conventional ARQ protocols. Moreover, the protocol do not suffer from the lack of throughput scalability for larger user populations.
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How this classification was reachedexpand
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 | 0.001 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".