Impulsive noise modeling with stable distributions in fading environments
Bibliographic record
Abstract
The paper introduces a statistical and physically based mechanism giving rise to /spl alpha/-stable noise models. We show that the additive interference which is present in many environments can be modeled as symmetric /spl alpha/-stable by assuming: (i) independent signaling (effects) from a large number of interferers of the same type (modulation); (ii) Poisson distribution of interferers in space; and (iii) inverse power attenuation of the signal strength with distance. Our approach to /spl alpha/-stable noise modeling is based on the LePage series representation as opposed to the influence function approaches. The formulas derived are used to predict noise statistics in environments with lognormal shadowing and Rayleigh fading. The LePage series framework allows us to investigate practical constraints in the system model adopted, such as the finite number of interferers and the nonhomogeneous Poisson fields of the interferers. We characterize the interference for multiple access communication systems in which the interferers are assumed to be Poisson-distributed in the plane.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".