Energy Allocation and Cooperation for Energy-Efficient Wireless Two-Tier Networks
Bibliographic record
Abstract
In this paper, we consider the resource allocation in two-tier wireless systems in which small-cell base stations harvest energy from renewable sources in addition to the conventional power grid. Moreover, we assume that each cell has access to an energy storage system with a limited battery capacity. We introduce new mechanisms that enable an efficient allocation of the available energy over time across the network. In doing so, we take into account the time-varying fading channel, the inter-cell interference and the fluctuations of harvested energy. In particular, we propose convergent offline algorithms to maximize the network energy efficiency while satisfying an average sum-rate constraint at each cell. Furthermore, we extend the resource allocation scheme by enabling an energy cooperation between the cells. By cooperating, they can exchange their harvested energy through a smart-grid power infrastructure. Using numerical simulations, we verify the convergence of the proposed algorithms and analyze the efficacy of the resource allocation and energy cooperation schemes.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".