A token-based connectivity update scheme for unmanned aerial vehicle ad hoc networks
Bibliographic record
Abstract
Code division multiple access mobile ad hoc networks (CDMA-MANETs) are envisioned to be the next-generation networking architecture for networking military platforms in a battlefield. In this paper we consider a CDMA ad hoc network consisting of multiple unmanned aerial vehicles (UAVs). We propose a token-based connectivity update scheme to solve the code collision problem in assigning code channels as well as the network link update problem for the CDMA UAV ad hoc network. Our proposed scheme uses a token message, which continuously circulates around the network in a non-predetermined order, to conduct assignment of code channels for each UAV. By using the broadcast properties of the wireless communication media, our proposed scheme is able to discover new or lost neighbors almost in real time. Moreover, the proposed token-based connectivity update scheme implements spatial reuse of code channels, which is mandatory in large-scale ad hoc networks due to the limited size of the CDMA code set. We then derive a theoretical result for approximating the connectivity update latency, which is further verified through computer simulations.
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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 | 0.001 | 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 | 0.001 |
| 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".