Capacity of Fading Channels Under Spectrum-Sharing Constraints
Bibliographic record
Abstract
Traditionally, the frequency spectrum is licensed to users by government agencies in a rigid manner where the licensee has the exclusive right to access the allocated band. Therefore, licensees are protected from any interference all the time. From a practical standpoint, however, an unlicensed (secondary) user may share a frequency band with its licensed (primary) owner as long as the interference it incurs is not deemed harmful by the licensee. In a fading environment, a secondary user may take advantage of this fact by opportunistically transmitting with high power when its signal, as received by the licensed receiver, is deeply faded. In this paper we investigate the capacity gains offered by this dynamic spectrum sharing approach when channels vary due to fading. In particular, we quantify the relation between the secondary channel capacity and the interference inflicted on the primary user. We further evaluate and compare the capacity under different fading distributions. Interestingly, our results indicate a significant gain in spectrum access in fading environments compared to the deterministic case.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".