Queue-Aware Small Cell Activation for Energy Efficiency in Two-Tier Heterogeneous Networks
Bibliographic record
Abstract
In heterogeneous networks (HetNets), the network energy efficiency is critically determined by the base station (BS) deployment density. In this paper, we consider a BS density optimization problem by turning on only a fraction of micro BSs according to an activation ratio to minimize the network average power consumption per area in a 2- tier HetNet. In contrast to previous studies where a BS is assumed to be transmitting packets all the time, such that the network power consumption monotonically increases as the BS density increases, we assume that each BS can be busy or idle depending on the dynamic packet arrivals. The network power consumption is thus closely related to the average traffic intensity of each tier. With the assumption of universal spectrum reuse, the average traffic intensity of each tier is found to be uniquely determined by a set of fixed-point equations, based on which the network average power consumption per area is characterized. Simulation results demonstrate that the network average power consumption per area can be minimized by properly tuning the activation ratio. It is further revealed that the optimal activation ratio increases as the mean packet arrival rate of each user increases.
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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".