On the Efficient Implementation of the Multiband Joint Detection Framework for Wideband Spectrum Sensing in Cognitive Radio Networks
Bibliographic record
Abstract
An efficient and low-complexity algorithm for implementing a newly proposed wideband spectrum sensing framework in cognitive radio systems is presented. The framework which is known as multiband joint detection identifies suitable secondary transmission opportunities while protecting the primary network from harmful interference imposed by the secondary network. It has previously been demonstrated that the optimization problem obtained from the framework can be made convex if certain practical constraints are applied. In order to have a more insightful view of the optimization process and make the implementation of the framework more time- and cost-effective, an efficient algorithm which searches for the optimal solution with much lower complexity compared to other commonly used numerical algorithms is proposed. It is established that the iteration-complexity and the complexity-per-iteration of the proposed algorithm increases linearly with the number of optimization variables (i.e. the number of narrowband channels). The proposed algorithm is evaluated via simulation and is shown to obtain the optimal solution quickly and efficiently.
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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 | 0.000 |
| 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".