Adaptive beam allocation for multimedia Ka-band satellite networks
Bibliographic record
Abstract
Field trials have demonstrated that the demand for broadband multimedia services can be addressed by multibeam satellite communications at the Ka band (30/20 GHz) and beyond. Design of beam coverage areas for the broadband multimedia satellite systems must address the need to support an inhomogeneous spatial and temporal user distribution as well as a wide range of quality of service requirements. While dynamic allocation of satellite capacity enhances the network efficiency of a conventional satellite system, the achievable throughput and the flexibility of resource management are both constrained by the fixed beam geometry. We propose an adaptive beam allocation algorithm which tunes the shape of the satellite beams to reflect user distribution. When power is constrained and the user population is homogenous with respect to their quality of service requirement, experimental results show that the adaptive allocation, compared to the traditional uniform beam allocation, enhances the efficiency of satellite resource utilization by enabling a larger average number of users to transmit without degrading average user throughput.
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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 | 0.001 |
| 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".