Grant Free Age-Optimal Random Access Protocol for Satellite-Based Internet of Things
Bibliographic record
Abstract
In satellite-based Internet of Things (S-IoT) system, the timely status updating of terrestrial sensing user equipments (UEs) to satellite could be hampered by the long propagation delay, especially in massive machine type communications (mMTC). To guarantee the information freshness in S-IoT, a new performance indicator called age of information (AoI) is exploited to analyze the average AoI (AAoI) in the overload case of mMTC, and a grant free age-optimal (GFAO) random access protocol is proposed to lower the AAoI. Specifically, the closed-form expression of AAoI is derived by tracing the instantaneous AoI evolution of each UE through Markov analysis. Then, the proposed GFAO random access protocol is proved to achieve a minimum AAoI and a maximum throughput in S-IoT, by adjusting the number of access time slots in each transmission frame in the overload case of mMTC. Extensive simulations are conducted to validate the theoretical analysis, and show that there exists different optimal value of access time slots in system load region from 0.2 to 3, which can minimize AAoI and maximize throughput in the proposed GFAO random access protocol.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".