A novel physical carrier sensing scheme for enhancing spatial reuse in multihop wireless networks
Bibliographic record
Abstract
Recently, tuning the physical carrier sensing threshold (CSth) has been proposed as an efficient mechanism to enhance the network throughput in an IEEE 802.11-based multihop ad hoc networks. The physical carrier sensing method reduces the likelihood of collision by preventing nodes in the vicinity of each other from transmitting simultaneously, while allowing nodes that are separated by a safe margin to engage in concurrent transmission. In this paper, we propose a distributed adaptive scheme through which nodes dynamically adjust their CSth to eliminate the likelihood of collisions from hidden terminals and in turn enhances spatial reuse by reducing the number of exposed terminals. Specifically, a node adjusts its CSth based on both its success/ failure history attempts and the information it receives from neighboring nodes through CTS packets. Moreover, to reduce the effect of exposed terminals, the proposed scheme employs the RTS/CTS exchange only for the purpose of informing neighboring nodes of their CSth but not to silence them. The proposed scheme adaptively performs a dynamic switch between the RTS/CTS access scheme and the basic scheme based on a predefined policy in order to avoid the additional overhead caused by the RTS/CTS exchange. Simulations results have demonstrated the significant throughput gains that can be achieved by the proposed scheme, compared with other methods in recent literature.
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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".