Two-Stage Spectrum Sharing With Combinatorial Auction and Stackelberg Game in Recall-Based Cognitive Radio Networks
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Bibliographic record
Abstract
The dynamic spectrum access (DSA) among multiple heterogeneous primary spectrum owners (POs) and secondary users (SUs) in recall-based cognitive radio networks is investigated in this paper. In our framework, SUs demand a different amount of spectrum for their transmissions. Each PO provides a portion of radio resources for leasing and also offers its own primary users (PUs) a certain degree of quality of service (QoS). Furthermore, POs are allowed to have different spectrum trading areas and as well as heterogeneous activities between POs' users. We propose a Two-stage resource allocation scheme with combinatorial Auction and Stackelberg Game in spectrum Sharing (TAGS) to deal with the allocation problem in such a complicated system. In the first stage, a spectrum allocation is decided by running a geographically restricted combinatorial auction without the consideration of spectrum recall. In the second stage, a Stackelberg game is formulated for all users to determine their best strategies with respect to the potential spectrum recall. Both theoretical and simulation results prove that TAGS provides a feasible solution for the problem and ensures the desired economic properties for all individuals.
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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 | 0.000 | 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 | 0.001 | 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