A continuous-time Markov chain model and analysis for cognitive radio 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
Cognitive radio concept has been widely researched to improve the spectrum usage efficiency. Appropriate modelling of the spectrum occupancy by both licensed and unlicensed users is necessary to do clear system analysis in a cognitive framework. In this paper, a continuous-time Markov chain model is developed to better describe the radio spectrum usage. The state space vector and the transition rate matrix that completely describe the system are obtained; a steady-state analysis is performed and the stationary state probability (SSP) vector is derived. In addition, we take into account the inaccuracy of the existing spectrum sensing model (missed opportunities), and derive an improved expression for the maximum throughput of secondary users as a function of the primary user traffic parameters and the achieved opportunity ratio (AOR). The optimum sensing period that maximises AOR is also analytically obtained. The proposed model and the derived expressions were examined through numerical analysis and compared with the existing models. This model is very general and applicable to systems with N secondary users in the vicinity of the primary user.
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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 | 0.001 | 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 | 0.000 | 0.001 |
| Open science | 0.001 | 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 it