On the Impact of Orbital Motion on Handoff and Coverage in Multi-antenna LEO Satellite Systems
Bibliographic record
Abstract
As fast-moving low Earth orbit (LEO) satellite communication systems gain increasing prominence, the significance of analytical performance models that account for mobility becomes more crucial than ever. Additionally, while considerable progress has been made in modeling the coverage performance of single-antenna LEO satellites, there is a noticeable gap when it comes to considering multi-antenna satellites. This paper presents a novel stochastic geometry framework to characterize the user coverage probability in a downlink LEO satellite network in the presence of multi-antenna satellites, handoffs (HOs), and the Shadowed-Rician fading model. We first determine the distribution of the desired and interfering channel power gains under zero-forcing beamforming. Then, we characterize the HO probability per unit time referred to as the HO rate under distance-based association. Next, we derive the handoff-aware coverage probability expression, and we validate our findings through numerical results obtained from Monte-Carlo simulations, offering insights into the effects of HO and multi-antenna processing on user coverage probability.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".