On the Beamforming Design and Transmit Power Analysis for Single- and Multi-Cluster NOMA
Bibliographic record
Abstract
This paper is on the beamforming design and performance analysis of the power-domain non-orthogonal multiple access (NOMA) systems. First, a closed-form linear beamforming design is proposed for single-cluster NOMA systems with two users to minimize the required transmit power with users' signal-to-interference-plus-noise-ratios (SINRs) guaranteed. The average power consumption and the power scaling law are derived for the proposed beamforming design. For multi-cluster NOMA, we exploit a two-stage beamforming design where the first stage eliminates the inter-cluster interference via zero-forcing (ZF) and the second stage aims at saving the required transmit power within each cluster by using the proposed single-cluster beamforming design based on the effective channel vectors. Numerical results are provided to show the superiority of NOMA transmissions with our proposed beamforming comparing to other transmission schemes in terms of the required transmit power and the outage performance.
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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 | 0.001 | 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".