Resource Allocation for Cognitive Radios in Dynamic Spectrum Access Environment
Bibliographic record
Abstract
We investigate the dynamic spectrum sharing problem among primary and secondary users in a cognitive radio network subject to QoS constraints for secondary users and interference constraints for primary users. For a scenario where only mean channel gains from secondary users to primary receiving points, which are averaged over short-term fading, are available, we derive outage probabilities for secondary users and interference constraint violation probabilities for primary users. Based on the analysis, we develop a framework to perform joint admission control and rate/power allocation for secondary users such that statistical guarantees on the violation probabilities of both the QoS and the interference constraints are achieved. Spectrum access by the secondary users can exploit the time-varying nature of the activity of the primary users, and thereby much higher throughput can be achieved compared to the case where primary users are assumed to be active at all time. Also, via extensive numerical analysis, throughput performances of primary and secondary users are investigated considering different levels of implementation complexity due to channel estimation.
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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 | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 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".