An Approach to Asynchronous Unsourced Random Access (URA)
Bibliographic record
Abstract
In this paper, we propose an approach to construct a fully asynchronous unsourced random access (URA) communication system. In addition to the typical characteristics of a URA system, such as absence of the user identification in the packet and focus on decoding of the message content, there is no limitation on the user transmission timing. The active users can transmit their packets at any time, on demand. The proposed system belongs to the class of preamble-payload URA formats. Contrary to the typical role of the preamble to serve as temporary user identifier in a URA system, in our proposed system the preamble serves the purpose of timing acquisition. The natural transmission asynchronicity reduces packet collisions. The remaining collisions are tackled by use of a small pool of distinct preambles. Our results demonstrate that, over a wide range of signal-to-noise ratios (SNRs), the number of active users supported by the proposed system is close to the number of users supported by an asynchronous URA system with genie-aided nacket timing.
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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 | 0.002 | 0.001 |
| Open science | 0.002 | 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".