Simultaneously Transmitting and Reflecting Reconfigurable Intelligent Surface Aided RSMA Communications: Outage Probability Analysis
Bibliographic record
Abstract
This paper investigates the use of simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) to assist the communication with multiple devices distributed according to a Poisson point process. First, using rate-splitting multiple access (RSMA) transmission scheme, the downlink STAR-RIS multi-user system is studied, and its fundamental statistics are provided. Then, by leveraging stochastic geometry tools, and adopting an approach based on the cumulative distribution function, the outage probability is obtained for the two types of devices, i.e., the ones in the transmission zone and those in the reflection zone. For such, the distributions of the channel gains and the devices’ distances are also characterized. The closed-form expressions with Meijer-G functions for the outage probability are provided in two cases for the STAR-RIS operation, energy splitting and mode switching. Simulation results and comparisons are provided, and the impact of various system parameters on the outage performance is analyzed. In particular, it is shown that as the RIS size, the RSMA power splitting factor, and the devices’ density, increase, the STAR-RIS aided RSMA helps achieve enhanced performance in both operation cases, i.e., energy splitting and mode switching.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".