Optimal Design and Energy Efficient Binary Resource Allocation of Interference-Limited Cellular Relay-Aided Systems With Consideration of Queue Stability
Bibliographic record
Abstract
The topic of subcarrier and power allocation in the downlink of an orthogonal frequency division multiple access decode-and-forward relaying system is presented with the objective of encompassing system stability and interference limitations in one inclusive problem. The introduced model is designed to maximize the overall throughput of the cell-edge users that are served by relay stations. We analyze the stability requirement of buffers in the base station and the corresponding relay stations, and define the rate constraints in order to guarantee queue stability without requiring a priori knowledge of arrival traffic's statistics. The explained model results in a nonconvex optimization problem, and therefore, we employ a time-shared technique to achieve the closed form solution, which is only applicable when subcarriers can be shared by the users during one time-slot. In the case where the subcarriers are not allowed to be time-shared, we introduce a computationally efficient optimal binary subcarrier and power allocation method, in addition to a power conservative allocation mechanism. Using geometric-programming and monomial approximation techniques, we show that the proposed conservative approach, although nonconvex, can be solved in polynomial time. We also study the impact of adjustable time-slot division and interference-tolerance parameters on improving system performance. The extensive simulation results demonstrate the success of the proposed methods in terms of stabilizing the queues, improving the throughput by 30% and energy efficiency gain by 90%, in comparison with the existing similar models in the literature.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".