The Concept of Time Sharing NOMA into UAV-Enabled Communications: An Energy-Efficient Approach
Bibliographic record
Abstract
This paper proposes a framework for the optimal power allocation during time sharing non-orthogonal multiple access (TS-NOMA) transmissions performed by an unmanned aerial vehicle (UAV) in the context of large-scale scenario. The objective of this proposed framework is to maximize the energy efficiency (EE) within the UAV communication range. The idea behind is to propose a communication system that merges the advantages of UAV communications with the ones offered by the TS-NOMA paradigm maximizing the downlink EE among users. The resulting model finds applicability in performing energy efficient transmissions into power-constrained communication scenarios such as in disaster communications. Performance investigations regarding the proposed framework show its capability in finding the optimal energy efficient configuration of power resources, respecting both the power constraints at the transmitter and the quality-of-service requirement of the users. Furthermore, the proposed framework resulted able to maintain a good level of throughput fairness among users in downlink.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".