Flipped Diversity Aloha in Wireless Networks with Long and Varying Delay
Bibliographic record
Abstract
The design of random media access control (MAC) renews great attention for emerging challenged wireless environments where the propagation delay is long and varying, such as satellite or underwater acoustic sensor networks. In these environments, the existing MAC solutions based on slotted transmissions, carrier sensing, or channel reservation by control packets are no longer favorable or even feasible. In this paper, we propose the Flipped Diversity Aloha (FDA) MAC protocol to tackle the challenges based on a new diversity transmission scheme. Different from the existing diversity transmission schemes, each data packet and its flipped version are transmitted back-to-back, and the receiver uses the Zigzag decoding technique to decode collided packets. The performance of FDA has been evaluated by analysis and simulation. The results show that, without time synchronization or handshaking requirements, the performance of FDA is unaffected by the duration or variation of the propagation delay, and it can substantially improve system performance in terms of throughput, packet loss ratio, and network admission region.
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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 | 0.000 | 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".