Distance Statistics of the Communication Best Neighbor in a Poisson Field of Nodes
Bibliographic record
Abstract
In a wireless network, while the signal attenuation due to the distance-related path loss is minimum between a node and its nearest neighbor, this is not the case for the overall attenuation when the fading effect is also taken into account. Hence, the communication best neighbor (CBN) of a node is defined as the neighbor of that node with which it has the highest channel power gain. Recently, the statistics of the physical neighborhood index of the CBN have been derived for a general fading environment in which the nodes have two-dimensional Poisson distribution. In this paper, the statistics of the distance between a node and its CBN as well as the joint CBN distance-index statistics are obtained for the same scenario. Then, the analytical expressions are specialized for the case where the communication channels follow the generalized gamma fading model. Also, the results are verified and illustrated by computer simulations and numerical results. Further, it is shown how the obtained analytical results can be used to identify the CBN more efficiently by limiting the search region and the number of neighbors that are examined.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".