Joint Power Allocation and Relay Selection in Cooperative Networks
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Bibliographic record
Abstract
In this paper, we study the joint power allocation and relay selection problem for multi-user amplify-and-forward (AF) cooperative networks. To increase the system's spectral efficiency under the orthogonal transmission assumption, each source-destination pair is constrained to be assisted by a small subset of a set of available relays. The aim of this work is to establish a framework that determines which relays to help which users and with how much power. In particular, we propose the joint schemes under two design criteria: i) maximization of user rates, and ii) minimization of the total transmit power at the relays. As the original problem formulations are shown to be nonconvex integer optimization problems, and thus, are combinatorially hard, we also propose an efficient convex relaxation approach to solve the problems with low complexity. Numerical results demonstrate the effectiveness of the proposed approaches.
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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 | 0.000 | 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