Bibliographic record
Abstract
Using relays in wireless networks can potentially lead to significant capacity increases. However, within an asynchronous multi-user communication setting, relaying might cause more interference in the network, and significant sum-rate deterioration may be observed. In this work the effect of cooperation in an interference limited, narrow-band wireless network is investigated. It is crucial to determine the optimal trade-off between the amount of throughput gain obtained via cooperation and the amount of interference introduced to the network. We quantify the amount of cooperation using the notion of a cooperative region for each active node. The nodes which lie in such a region are allowed to cooperate with the source. We adopt the decode-and-forward scheme at the relays and use the physical interference model to determine the probability that a relay node correctly decodes its corresponding source. Through numerical analysis and simulation, we study the optimal cooperative region size to maximize the network sum-rate and energy efficiency, based on network size, relay availability, node decoding threshold, and destination reception capability. It is shown that optimized system performance in terms of the network sum-rate and the power efficiency is significantly improved compared with cases where relay nodes are not exploited or where the cooperative region size is suboptimal.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".