Performance Analysis of Hybrid Relay RIS-Assisted NOMA Networks
Bibliographic record
Abstract
Wireless communications have progressed remarkably towards Sixth-Generations (6G) which are projected to utilize higher frequencies than those of Fifth-Generation(5G) wireless communications. This advancement will facilitate greater data transmission rates and capacity. In this paper, we introduce an innovative Hybrid Relay-Reflecting Intelligent Surface (HR-RIS) approach for Multiple-Input Multiple-Output (MIMO) systems aided with Non-Orthogonal Multiple Access (NOMA) technology, incorporating a limited number of elements equipped with power amplifiers to operate as active relays, and other elements dedicated to passive signal reflection. This HR-RIS, enhanced with NOMA, is proposed to maximize the spectral efficiency (SE), and the optimization process on the HR-RIS both active and passive elements is facilitated by an Alternating Optimization (AO) strategy. Simulations and numerical results prove that the HR-RIS aided with NOMA can significantly surpass the SE performance of standard RIS. The advantages and effectiveness of the proposed HR-RIS deployment Aided with NOMA are both theoretically and numerically substantiated.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".