Bibliographic record
Abstract
The key agreement problem over a state-dependent wiretap channel with a parallel one-way public channel in the forward direction is studied. It is assumed that the channel state information (CSI) is non-causally known at the transmitter. In this paper, the effect of the public channel and the CSI on the key generation is investigated, and the key capacity as a function of public channel capacity CP, CK(CP), is sought for a discrete memoryless (DM) model and a Gaussian model, in which the CSI is an additive white Gaussian interference. For each model, a lower bound and an upper bound on the key capacity are derived, and CK(∞) is achieved as the bounds are asymptotically tight. For any DM wiretap channel, it is shown that there exists a finite capacity CP* beyond which CK(CP) = CK(CP*). If the CSI is also fully known at the legitimate receiver, it is proved that the public channel has no effect on the key capacity. For the Gaussian model, the achievable key rate is a strictly increasing function of CPin general. In addition, CK(CP) is attained in both the low signal-to-interference ratio (SIR) regime and the high SIR regime. In the low SIR regime, the public channel cooperates with the transmitter for the key generation from the known interference. In the high SIR regime, however, the public channel makes negligible contribution to the key generation.
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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 | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.010 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".