Discrete location‐aware resource allocation for underlay device‐to‐device communications in cellular networks
Bibliographic record
Abstract
Device‐to‐device (D2D) communications underlaying a cellular network is an efficient way to enhance spectral efficiency via resource sharing between D2D and cellular users (CUs). In this study, a discrete location‐aware (DLA) interference model for D2D users is presented to allocate cellular resources. The vicinity of a CU is discretised into multiple regions, and the number of active D2D users in each region is constrained to satisfy the CU QoS requirements. Considering the locations of D2D users affecting the interference to CUs and thus the achievable rate, the formulated non‐linear 0–1 knapsack resource allocation (RA) problem is divided into two subproblems: (i) the optimal amount of shared resources between the two types of users; (ii) the optimum subset of D2D users which transmit . The conditions of D2D users spatial deployment and resources reuse portion to achieve the solutions of the two subproblems are theoretically derived and proven. Then a DLA‐RA algorithm is proposed to solve the corresponding subproblems in both single CU and multiple CUs cases. Extensive simulations results are presented which verify the effectiveness of the proposed DLA interference model and the RA scheme.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.004 | 0.001 |
| 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".