Mesh adaptive direct search approach for D2D resource management
Bibliographic record
Abstract
Abstract Device‐to‐device (D2D) communications are being considered a way forward to achieve higher data rate targets for futuristic wireless networks. D2D introduces interference among cellular users and D2D users. A joint resource allocation (JRA) strategy in cellular network with D2D functionality can definitely enhance overall data rate. The strategy under consideration maximizes the overall data rate of cellular network besides meeting threshold of power and interference constraints. The JRA is a class of mixed integer non‐linear constraint optimization problems and is NP hard. Because of discrete nature of variables in the problem, optimal solution performs extensive search of integer variables, and problem becomes exponentially complex with the increasing number of user pairs. In this paper, mesh adaptive direct search algorithm is applied to solve the aforementioned problem. The algorithm is suitable for complex problems of combinatorial nature to solve the JRA strategy in D2D. The proposed algorithm converges to optimal solution within acceptable computational iterations. Simulation results of system capacity and interference also demonstrate the suitability of the proposed approach viz‐a‐viz other algorithms. Copyright © 2016 John Wiley & Sons, Ltd.
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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".