Energy-Efficient Resource Allocation for OFDMA Cellular Networks With User Cooperation and QoS Provisioning
Why this work is in the frame
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Bibliographic record
Abstract
In this paper, an energy-efficient resource allocation scheme is designed for orthogonal frequency-division multiple-access cellular wireless networks with multiuser cooperation. Joint relay selection, subcarrier allocation and pairing, and power-allocation algorithms are developed with the objective of maximizing the energy efficiency of the system considering the quality-of-service requirements of the users. The optimization problem is a mixed-integer nonlinear program (MINLP), which is generally very difficult to solve in its original form. The energy efficiency metric is a fractional and nonlinear function, which complicates the problem further. We provide a novel optimization framework to solve such nonlinear and nonconvex optimization problems. The MINLP optimization problem is reformulated to a convex problem by relaxing the integer variables and by introducing the "Dinkelbach" method to tackle the nonlinear fractional objective function. We prove that our proposed solution of the relaxed problem is optimal and has integer values. Based on the dual-decomposition method, we propose a solution to the joint optimization problem, which is optimal and computationally efficient with polynomial-time complexity. Numerical results demonstrate the effectiveness of our proposed scheme.
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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 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it