Enhanced Busy-Tone-Assisted MAC Protocol for Wireless Ad Hoc Networks
Bibliographic record
Abstract
In wireless multihop ad hoc networks, the hidden terminal problem severely degrades the overall performance. On the other hand, most existing solutions cause larger blocking areas and hence a more severe exposed-terminal problem. In this paper, we present a new Enhanced Busy-tone Multiple Access (EBTMA) medium access control (MAC) protocol. The proposed protocol minimizes the negative impact of both the hidden-terminal and the exposed-terminal problems with the assistance of an out-of-band busy tone signal. The new protocol can also enhance the reliability of packet broadcast and multicast which are very important for many network control functions such as routing. Unlike the previous busy-tone schemes, such as the original Busy-tone Multiple Access (BTMA) protocol, our proposed protocol uses a non-interfering busy- tone signal in a short period of time, in order to notify all hidden terminals without blocking a large number of nodes for a long time. Our analysis, verified by simulation results, demonstrates that the proposed MAC protocol outperforms the existing ones and it can greatly improve the performance of wireless ad hoc networks. In addition, the proposed EBTMA protocol can co-exist with the existing 802.11 MAC protocol, so it can be incrementally deployed.
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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 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".