Optimal Energy Management in Hybrid Energy Small Cell Access Points
Bibliographic record
Abstract
In this paper, we consider a multiantenna small-cell access-point serving multiple users on the downlink and uplink sides using the frequency division duplex scheme. The access point is powered by both renewable and non-renewable energy sources. The objective of this paper is to process the frequency division duplex frame by drawing the minimum amount of energy from the non-renewable energy source while guaranteeing the quality of service of downlink transmission and decoding all the received uplink packets. Assuming that the energy used for sampling and decoding the received packets is not negligible, the optimal transmit power allocation and received packet decoding policy is investigated first in an offline setting and then in an online setting. An iterative offline algorithm based on dual decomposition method is proposed to find the optimal policy. In the online setting, an optimal high-complexity solution using dynamic programming approach is developed. Then, a reduced complexity suboptimal online algorithm using dual decomposition is proposed. Finally, two more suboptimal and low-complexity online algorithms for maximizing the ratio of throughput and non-renewable energy, and fairness metric are further addressed. Numerical simulations evaluate the performance of the proposed offline and online algorithms and show the efficiency of our proposed algorithms.
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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 | 0.001 | 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".