Impact of intra- and inter-RAT offloading on the spectrum/energy efficiency of HetNets
Bibliographic record
Abstract
This paper addresses the problem of simultaneously achieving high spectral efficiency (SE) and energy efficiency (EE) in the heterogeneous radio access technology (RAT) environment via biased intra- and inter-RAT offloading. An analytical framework is developed for investigating the SE and EE performance of a two-RAT heterogeneous network (HetNet), based on which it is shown that the feasibility of increasing the SE and EE via offloading is strongly dependent on the load level and the biased offloading factors. For jointly maximizing the SE and EE, a multi-objective optimization problem subject to quality of service (QoS) constraints is formulated and solved to give the Pareto optimal operational regime in terms of the network parameters. Following this, the constrained Pareto regime is used to quantify the tradeoff between SE and EE as an opportunity cost measure. By opportunistically adapting the small cell BS density and biased offloading factors to the load conditions, we numerically show the range of load values that achieves a good balance in the SE-EE tradeoff while satisfying the specified users' QoS requirements.
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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".