On the Achievable Capacity of Cooperative NOMA Networks: RIS or Relay?
Bibliographic record
Abstract
In this letter, a novel reconfigurable intelligent surface (RIS)- and relay-assisted cooperative network with non-orthogonal multiple access (NOMA) is proposed, where the line-of-sight (LoS) and non-LoS (NLoS) scenarios are both considered for different locations of users. For the proposed cooperative NOMA systems, we first analyze the capacities of the RIS- and relay-assisted downlinks, respectively. Since it is difficult to obtain the closed-form expressions in terms of the achievable capacity, we apply the central limit theorem (CLT) and Jensen’s inequality to determine a tight upper bound for the channel gain. Then, we focus on the solutions in relay and RIS providing more capacity advantages. Numerical and simulation results verify the correctness of the derived expressions and the superiority of our proposed model. Finally, we clarify that, with different conditions of the transmit scenarios, RIS- and relay-assisted cooperative networks show their various advantages and limitations.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".