Bibliographic record
Abstract
Cognitive Networks have been proposed to opportunistically discover and exploit licensed spectrum bands, in which the secondary users' (SU) activity is subordinated to primary users (PU). Depending on the nature of interaction between the SU and PU, there are two frequently encountered types of spectrum access: \emph{underlay} and \emph{interweave}. While a lot of research effort has been devoted to each mode, there is no clear consensus about which type of access performs better in different scenarios and for different metrics. To this end, in this paper we approach this question analytically, and provide closed-form expressions that allow one to compare the performance of the two types of access under a common network setup. We focus on the average delay as the key metric, which we analyze using queueing theory. This allows an SU to decide when one type of access technique provides better performance, as a function of the metric of interest and key network parameters. What is more, based on this analysis, we propose a dynamic (hybrid) policy, that can decide at any point to switch from one type of access to the other, offering up to 50% of additional performance improvement, compared to the optimal "static" policy in the scenario at hand. We provide extensive validation results using a wide range of realistic simulation scenarios.
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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".