An Energy Efficient Overlay Cognitive Radio Approach in UAV-Based Communication
Why this work is in the frame
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Bibliographic record
Abstract
Most of the drone-based applications require a time-limited access to the spectrum to complete data transmission due to limited battery capacity of these flying units. This paper proposes an efficient spectrum and energy management solution by integrating the overlay cognitive radio technology. Therefore, we aim to use the drone as a secondary node and target to determine an optimized three-dimensional location and a resource control solution by which it can complete its data transfer and in parallel support the primary communication. To this end, a non-convex optimization problem is developed. The obtained solution minimizes the total energy consumption of the drone and, at the same time, maintains the required data rate level of the spectrum's owner. A resource allocation procedure and swarm intelligence-based positioning algorithm are jointly designed for this purpose. Numerical results show the efficiency of the proposed approach in terms of energy consumption savings and additional transmission opportunities as compared to other schemes.
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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 | 0.000 |
| 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 it