Sum-Rate Results in Point-to-Multipoint Cognitive Networks: Effect of Path Loss
Bibliographic record
Abstract
We consider simultaneous operation of primary and secondary point-to-multipoint networks in the same frequency band when interference in treated as noise. The variations in channel and interference gains are characterized by path loss and multipath fading. Scaling laws for the primary and secondary sum-rates are derived when the scaling is in terms of the number of primary users. In order to maintain a quality of service requirement for the primary system and simultaneously obtain positive sum-rate for the secondary, a scheduling strategy can be applied to activate users in each network based on their interference gains only. Interestingly, using this strategy, the scaling laws for sum-rates are independent of the path loss consideration of the channel, i.e., the primary and secondary networks can achieve the same asymptotic sum-rates as shown in when only multipath fading is considered. Consequently, while the primary network is protected, we can obtain significant improvement in the asymptotic secondary sum-rate compared to that achievable under channel sharing via time division (TD).
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".