Power Control for Secrecy Fairness-Aware Regenerative Relaying in Untrusted NOMA
Bibliographic record
Abstract
Non-orthogonal multiple access (NOMA) has been recognized as a promising multiple access technique to improve the spectral efficiency of the fifth-generation (5G) and beyond networks. However, the successive interference cancellation (SIC) based decoding used at the receivers makes NOMA prone to critical security risks. In this paper, we consider a regenerative relay-assisted dual-user downlink NOMA communication model. To ensure the robustness of the model, we also take into account the error propagation in SIC occurring in the decoding process. Our design goal being to provide security to both users, we propose an optimal power management strategy, so as to maximize the secrecy rate of the users under the impact of imperfect SIC. The optimal power allocation solution is obtained such that positive secrecy rate is achieved at both of the end receivers, while accounting for SIC errors. Analytical expressions of the secrecy rates are derived to analyze the secrecy performance. Simulation results are also presented, and provide key insights on the obtained secrecy rate and power allocation coefficients with residual interference. The achieved gains prove that the proposed model can substantially improve the secrecy performance.
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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 | 0.000 |
| 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".