Bibliographic record
Abstract
A decentralized network of one Primary User (PU) and several Secondary Users (SU) is studied. PU is licensed to exploit the resources, while the party of SUs intend to share the resources with PU. Each SU must guarantee to not disturb the performance of PU beyond a certain level, while maintaining a satisfactory quality of service for itself. It is proposed that each secondary transmitter adopts a Randomized Masking (RM) strategy with full average transmission power where it remains silent or transmits a symbol in its codeword independently from transmission slot to transmission slot. We consider a setup where the primary transmitter is unaware of channel coefficients, code-books of secondary users and the number of secondary users. SUs are anonymous to each other, i.e, they are unaware of each others' code-books, however, each SU is smart in the sense that it is aware of the code-book of PU, channel coefficients and the number of active SUs. Invoking the concept of ε-outage capacity, we define the (ε,ν)-admissible region as the set of masking probabilities for each SU such that the probability of outage for PU is maintained under a threshold \varepsilon in a case where PU sets its transmission rate at a fraction ν of its ε-outage capacity as if there were no SUs in the network. The masking probability of SUs is designed through maximizing the average (with respect to channel coefficients) achievable rate per SU over the (ε,ν)-admissible region. In our analysis, the primary receiver treats interference as noise, however, each secondary receiver has the option to decode and cancel the interference caused by PU, while treating the signals of other SUs as noise. In another approach, referred to as Continuous Transmission with Power Control (CTPC), each SU transmits continuously (no masking is applied), however, it adjusts its transmission power in order to yield the largest value for average achievable rate per SU. The schemes RM and CTPC are compared for different values of transmission power for each SU and PU and distance between different users. It is observed that neither of RM or CTPC always outperforms the other in various scenarios in terms of the underlying system parameters. A combination of RM and CTPC referred to as Randomized Masking with Power Control (RMPC) is also investigated where each SU controls both its probability of masking and average transmission power. It is demonstrated through simulations that RMPC can outperform both RM and CTPC.
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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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".