Stackelberg game approach for wireless virtualization design in wireless networks
Bibliographic record
Abstract
We propose a wireless virtualization framework based on the Stackelberg game model for resource allocation in downlink orthogonal frequency division multiple access (OFDMA) wireless networks. Specifically, the wireless virtualization model enables an infrastructure provider (InP) to effectively lease radio resources to multiple mobile virtual network operators (MVNOs) through adaptively setting resource prices whereas the MVNOs selfishly optimize the resource allocation to maximize their utilities. The Stackelberg game approach is employed to solve the underlying hierarchical problems where the InP acts as a leader while the MVNOs play the roles of the followers. In particular, we derive the Stackelberg equilibrium (SE), at which no player has incentive to deviate unilaterally. Extensive numerical results are presented to confirm the efficacy of our proposed framework in balancing the achievable utilities of the InP and MVNOs compared to other traditional pricing 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 | 0.001 | 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 | 0.001 | 0.001 |
| Open science | 0.002 | 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".