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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".