Cognitive Radio with Imperfect Spectrum Sensing: The Optimal Set of Channels to Sense
Bibliographic record
Abstract
Opportunistic channel sensing and access problem of a secondary user with multiple potential primary channels is investigated. The secondary user can sense a limited number of channels, and channel sensing is imperfect. If the secondary user can access all channels sensed free, it is proved that the secondary user should sense the channels with the largest rewards, where the reward of a channel is the reward that the secondary user can acquire if it senses the channel and accesses the channel if the channel is sensed free. If the secondary user can access only a limited number of sensed-free channels, in general it may not be optimal to sense the channels with the largest rewards. However and interestingly, for some special cases (for example, when all the channels have the same detection probability), simple rules are given for the optimal selection of channels to sense. For the general case, methods are given to reduce the searching complexity for the optimal set of channels to sense.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 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".