Optimal Hidden Node Area for Enhancing Routing Protocol Performance in IEEE 802.11 Multihop MANETs
Bibliographic record
Abstract
The prevalence of hidden node areas in IEEE 802.11 multihop MANETs continues to hinder the performance of routing protocols. This letter presents an analytical model that relates the hidden node area to the hop distance between two communicating nodes. Unlike descriptions from the literature, we describe the hidden node area in terms of multiple layers and the different levels of interference contributed by each layer. We then develop mathematical expressions to determine the probability of successful delivery and end-to-end delay of a packet transmitted over multiple hops to a receiver node exposed to hidden nodes, as a function of hop distance. The numerical results show that decreasing the hop distance increases the probability of successful packet reception at a receiver, at the cost of increased end-to-end delay. However, using a specified delay objective, routing protocols can institute a hop distance threshold metric to limit the number of transmissions that produce collisions in the hidden node area and, thus, maximize their performance.
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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 | 0.007 |
| 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 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".