Game Theoretic Analysis of Post Handoff Target Channel Sharing in Cognitive Radio Networks
Bibliographic record
Abstract
Handoff in cognitive radio networks (CRNs) is a situation that arises whenever a secondary user (SU) has to switch from its current channel to a new target channel in case the primary user (PU) reclaims the current channel. Often when a SU switches to a target channel, it finds that it has to share the target channel with the coexistent users. These coexistent users can either be the interrupted or non-interrupted SUs who also wish to share the same channel. Long waiting in a queue or simultaneous access to the channel may decrease the SU's and network's throughput considerably. The SUs may even behave selfishly to maximize their own throughput. This paper analyzes the interactions and behavior of the SUs during the target channel sharing through non-cooperative, mixed strategic, and cooperative games. The benefits of the SUs and the overall network is analyzed by finding the Nash equilibrium and the Nash bargaining solution (NBS) for the non-cooperative, mixed strategy, and cooperative game respectively.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".