Energy-Efficient Power Allocation for Hybrid Multiple Access Systems
Bibliographic record
Abstract
In this paper, energy-efficient power allocation (PA) is studied for a hybrid system with non-orthogonal multiple access (NOMA) integrated into orthogonal multiple access (OMA). The considered energy efficiency (EE) maximization problem belongs to non-convex fractional functions. To tackle it, the corresponding spectral efficiency maximization problem for a given transmit power is first considered. By changing the variables from power coefficients to user rates, the non-convex problem is transformed into a convex one, for which a closed-form solution is obtained. On this basis, the optimal transmit power is determined to maximize the EE of the system by exploiting the property of pseudo-concave functions. Numerical results are presented to validate the effectiveness of the proposed energy-efficient PA strategy, as well as the superiority of the hybrid MA over OMA in terms of EE.
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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 | 0.000 |
| 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 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".