Multi-ARIS Backscatter Enabled Downlink NOMA Communication for Cognitive Radio Systems
Why this work is in the frame
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Bibliographic record
Abstract
This paper investigates an active reconfigurable intelligent surface (ARIS) backscatter communication (BackCom) enabled downlink NOMA scheme in a cognitive radio (CR) system. Specifically, a dedicated primary beacon (PB) is deployed to serve the primary user while providing carrier signal for ARIS-BackCom units, which act as secondary transmitters (STs) to communicate with secondary users (SUs). Notably, the deployment of multiple ARIS-BackCom devices not only reduces the radio frequency (RF) component costs in the secondary network, but also provides multiple reflective link array gains, and overcomes the double-fading phenomenon effect. Based on the established system framework, we formulate the joint optimization problem of the beamforming vectors at the PB and the STs to maximize the weighted sum rate of the SUs while ensuring quality of service for the PU. The highly-coupled non-convex problem is decomposed into three sub-problems, which can be effectively addressed jointly using fractional programming, Lagrangian dual transform, difference-of-convex, and successive convex optimization methods. Finally, the comprehensive simulation results demonstrate that, in comparison with the traditional passive RIS-BackCom network, the proposed scheme significantly boosts the network’s weighted sum rate (WSR) by a minimum of 60%.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it