Joint channel and power allocation in underlay multicast device-to-device communications
Why this work is in the frame
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Bibliographic record
Abstract
In this paper, we present a framework of resource allocations for multicast device-to-device (D2D) communications underlaying a cellular network. The objective is to maximize the sum throughput of active cellular users (CUs) and feasible D2D groups in a cell, while guaranteeing a certain level of the signal-to-interference-plus-noise ratio (SINR) for both the CUs and D2D groups. We formulate the problem of power and channel allocations as a mixed integer nonlinear programming (MINLP) problem where each D2D group can reuse the channel of at most one CU and each CU can share their resources with at most one D2D group. A maximum weight bipartite matching based scheme is developed to assign the optimal channel for each feasible D2D group to reuse. A heuristic algorithm is then proposed which has less complexity compared to the matching algorithm. The performance of both schemes is evaluated through simulations. Numerical results demonstrate that the proposed heuristic scheme outperforms other heuristic schemes in the literature and can achieve close-to-optimal performance.
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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 | 0.000 |
| 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 it