Interference-Limited versus Noise-Limited Communication Over Dense Wireless Networks
Bibliographic record
Abstract
A network of𝓃wireless communication links is considered. Rayleigh fading is assumed to be the dominant factor affecting the strength of the channels between nodes. In previous works it is shown that the maximum throughput of this network over all link activation strategies scales aslog 𝓃. However, it is achieved by assigning a vanishingly small rate to each active link. The objective of this paper is to analyze the achievable throughput of the network when the data rate of each active link is constrained to be a constantλ > 0. A link activation strategy is proposed and analyzed using random graph theory. In the interference-limited regime, a throughput scaling asτ log 𝓃is achievable, where the scaling factor τ approaches 1 asλ → 0or λ → ∞. This implies the asymptotic optimality of the proposed scheme. In the noise-limited regime, it is shown that rate-per-links scaling aslog(Δ0ρ)are achievable, whereΔ0is a constant andρis the transmit signal to noise ratio. However, in this case the throughput decreases by a factor oflog log 𝓃as compared to the interference-limited regime.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.001 |
| 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".