Performance Analysis of Co-Operative Beacon Sensing Strategies for Spatially Random Cognitive Users
Why this work is in the frame
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Bibliographic record
Abstract
Primary user (PU) beacons must be detected by cognitive users (CUs) to access spectrum holes, and misdetection results in interference on PUs. To alleviate this problem, sensing results of spatially separated CUs can be combined to make a final decision. In this paper, we analyze several such co-operative beacon sensing (CBS) strategies given spatial randomness of CU and PU nodes, which is modeled via independent homogeneous Poisson point processes. We consider two cases of beacon emitter placement: 1) at PU-transmitters and 2) at PU-receivers. We analyze three separate local beacon detection schemes and propose five CBS schemes. They require the sharing of CU results via a control channel subject to Rayleigh fading and path loss, and making a final decision via the OR rule. By using stochastic geometry, we derive both the misdetection probability, the false alarm probability, and the primary outage and show that impressive gains are achievable. For example, with PU-receiver beacons, CBS reduces misdetection by a factor of 104. In contrast, with PU-transmitter beacons, the reduction diminishes with the increased cell radii, but there exists an optimum cooperation radius.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 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