Joint In-Orbit Computation and Communication for Minimizing Download Time From LEO Satellites
Bibliographic record
Abstract
Downloading a large amount of data from a low Earth orbit satellite to a ground station can be challenging due to the limited contact window, dynamic channel quality, solar energy supply, and thermal management without an atmosphere. Considering such dynamics, this paper proposes a joint design of in-orbit computation and communication for download time minimization. We combine the non-convex thermal constraints and energy constraints into unified energy budget constraints with upper bound approximation, and computational efficiency is achieved by decomposing the resulting large-scale problem into a non-convex communication sub-problem, a convex computation sub-problem solvable with interior point method and a master problem that optimizes the energy budget allocation between computation and communication. The communication sub-problem is solved with a generalized-benders-decomposition-based algorithm that decouples downlink scheduling and power allocation based on a closed-form solution of optimal dual variables in the power allocation primal problem. And the master problem is solved with ternary search by proving the minimal download time is quasi-convex with respect to the energy budget allocation between computation and communication. Simulation results demonstrate that the proposed solution effectively reduces the download time, especially under strict energy constraints and severe channel variations.
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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 | 0.000 | 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 | 0.000 |
| 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 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".