Performance of a knockout switch for multimedia satellite communications
Bibliographic record
Abstract
This paper investigates the performance of a multiple-beam satellite communications system using an on-board knockout switch to support multimedia services. Aggregate voice or video traffic is modeled as a 2-state Markov modulated Poisson process (MMPP) while two models for aggregate data traffic, MMPP and Pareto-modulated Poisson process (PMPP), are used to examine the effects of traffic burstiness and long-range dependent behavior. Multiple-frequency time division multiple access (MF-TDMA) is used on the uplink in conjunction with a dynamic capacity allocation scheme. Higher priority is given to voice, and video realtime traffic to avoid delay variation. An on-board downlink queue for jitter-tolerant data is provided to achieve high statistical multiplexing gain. Simulation results show that packet loss due to the knockout contention scheme is much lower than that due to the limited capacity on the uplink and downlink. This makes the knockout architecture attractive for on-board switching to achieve low complexity.
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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 | 0.002 |
| 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".