Congestion Pricing in Wireless Cellular Networks
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
While the demand for wireless cellular services continues to increase, radio resources remain scarce. As a result, network operators have to competently manage these resources in order to increase the efficiency of their Wireless Cellular Networks (WCN) and meet the Quality of Service (QoS) of different users. A key component of Radio Resource Management (RRM) is congestion control. Congestion can severely degrade the performance of WCN and affect the satisfaction of the users and the obtained revenues. Several congestion control techniques have been proposed for WCN. These techniques, however, do not provide incentives to the users to use the wireless network rationally, and hence they cannot solve the problem of congestion. Recently, there has been some research on providing monetary incentives to the users through congestion pricing to use the wireless network rationally and efficiently. Congestion pricing is a promising solution that can help alleviate the problem of congestion and generate higher revenues for network operators. This paper surveys recent research work on congestion pricing in WCN. It also provides detailed discussions and comparisons of the surveyed work as well as open problems and possible future research directions in the area.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it