Distributed energy-efficient inter-cell interference control with BS sleep mode and user fairness in cellular networks
Bibliographic record
Abstract
Inter-cell interference (ICI) and energy efficiency are two important issues in future generation cellular networks. These two issues are studied separately in most of previous works. Since both ICI and energy efficiency have great impacts on user quality of service (QoS) and energy consumption, they should be jointly studied and optimized in a common framework. In addition, most existing centralized schemes solving the ICI and energy efficiency problems may suffer from signaling overhead, outdated dynamics information, and scalability issues. In this paper, we proposed a common framework to dynamically allocate spectral resource to mitigate ICI and to save energy consumption at the same time. Base station (BS) sleep mode and fairness among users are considered in this paper. We first formulate the ICI and energy efficiency issues as a centralized optimization problem, and then we derive a distributed algorithm. Simulation results are presented to show the effectiveness of the proposed 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 | 0.000 | 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".