WSN07-5: Performance of Directional MAC Protocols in Ad-Hoc Networks over Fading Channels
Bibliographic record
Abstract
The application of directional antennas in mobile ad-hoc networks (MANETs) has proved to offer large throughput gains relative to single-antenna systems. Recent works on directional medium-access-control (MAC) protocols have been only focused on their performance over additive white-Gaussian noise (AWGN) channels. In this paper, we evaluate the performance of directional MAC protocols when the channel is modeled as a slow-fading one. In this case, directional antennas are used for the transmission of data frames while control frames are sent using an omnidirectional antenna. Considering a slow-fading channel, our results show large throughput improvements when using directional MAC protocols relative to the IEEE 802.11 standard. Furthermore we show that the throughput loss on the fading channels relative to the AWGN channel, can be well compensated using antenna arrays. All our results show that the use of directional antennas at the mobile station can improve the channel efficiency in an ad-hoc network.
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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 | 0.001 |
| 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".