An Age-Critical LEC-CFDP Scheme for Dual-Hop Space-Air-Ground Integrated Networks
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Bibliographic record
Abstract
The upcoming space-air-ground integrated network (SAGIN) can provide status updates relaying for ground user equipment (UEs). However, the SAGIN cannot utilize traditional hybrid automatic retransmission request (HARQ) for reliable transmission due to the high bit error rate (BER) and long propagation latency. In this paper, we propose the age-critical long erasure code-CCSDS file delivery protocol (LEC-CFDP) schemes with the metric of age of information (AoI) to realize timely status updates in dual-hop SAGIN. We first propose the uniform LEC-CFDP (U-LEC-CFDP), where the UE and satellite can uniformly insert one LEC packet in every <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$(L-1)$</tex> information packets, and the receiver can utilize the LEC packet to recover the lost packets and avoid retransmission. Moreover, the satellite can immediately forward the successively recovered information packets to the destination, named U-LEC-i CFDP, and a close-form expression of peak AoI (PAoI) for the U-LEC-i CFDP is derived. To further improve PAoI, we model a partially observable Markov decision process (POMDP) problem to analyse optimal <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$L$</tex> for our dynamic LEC-i CFDP (D-LEC-i CFDP), and design an effective Point-based Informed Bound (PIB) algorithm to update optimal <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$L$</tex>. Simulation results show that the D-LEC-i CFDP scheme can lower the expected end-to-end delay and PAoI in comparison with U-LEC-CFDP schemes.
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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 | 0.000 | 0.000 |
| 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 | 0.002 |
| 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 it