Joint subcarrier and power allocation in downlink OFDMA systems: an multi‐objective approach
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Bibliographic record
Abstract
ABSTRACT In this paper, we present a new technique for resource allocation in multi‐user orthogonal frequency division multiple access systems. The goal is to maximise the minimum data rate available to any user while minimising the total transmitted power. In order to achieve an optimal solution and capacity bounds, the subcarrier and power should be allocated simultaneously. Multi‐objective genetic algorithm can be used for joint allocation of subcarriers and power in such a case, and in this paper, it is achieved using non‐dominated sorting genetic algorithm‐II. The simulation results indicate that the proposed algorithm achieves high data rates as compared with previous algorithms. The algorithm allocates both subcarriers and bits jointly without being computationally expensive. The faster convergence of the algorithm to near optimal value, as compared with previous algorithms, is indicative of its less complexity. Copyright © 2013 John Wiley & Sons, Ltd.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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