Cooperative Rate Splitting Multiple Access for Active STAR-RIS Assisted Downlink Communications
Bibliographic record
Abstract
This letter explores the influence of an active Simultaneously Transmitting and Reflecting Reconfigurable Intelligent Surface (STAR-RIS) in supporting Cooperative Rate Splitting Multiple Access (C-RSMA) in a downlink wireless network. We consider a scenario where a base station (BS) with multiple antennas utilizes the active STAR-RIS to aid weak and strong users. Strong users also serve as full-duplex relays to transmit the common stream to weak users. By jointly optimizing BS beamformers, active STAR-RIS reflection and transmission, stream split, and strong users’ transmit power, we maximize the network sum rate while satisfying minimum rate requirements, active STAR-RIS hardware constraints and power budgets at the BS, the active STAR-RIS and at each strong user. An alternating optimization algorithm employing successive convex approximation is proposed, and simulations showcase its significant gains over baseline approaches.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.005 | 0.001 |
| 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".