A simple real-time handover management in the mobile satellite communication networks
Bibliographic record
Abstract
Low earth orbit (LEO) satellite networks are capable of providing global or regional mobile services for a large number of users. Since the user's service duration may be greater than the coverage time of a LEO satellite, the user may be handed over to another visible satellite to prevent interruption of the ongoing communication. On the other hand, a mobile user may be covered by more than one satellite at the instant of connection handover. When the user is about to be handed over to another satellite, the serving satellite minimizing the number of handovers would in general be the one that provides the largest service time which is not necessarily equal to the coverage time of the very satellite. In this paper, we propose a new handover algorithm which exploits both the Global Positioning System (GPS) infrastructure and satellite diversity to provide a simple and real-time handover management in LEO satellite networks. The proposed algorithm not only minimizes the expected number of satellite handover, but is also efficient and easy to be implemented in hand-held devices, thus facilitating the mobile users' access to the satellite networks. Numerical simulations performed for two typical mobile satellite networks, viz. Iridium and Globalstar, corroborate the advantages gained by the proposed algorithm.
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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 | 0.001 | 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".