Power Allocation and Link Selection for Multicell Cooperative NOMA Hybrid VLC/RF Systems
Bibliographic record
Abstract
This letter proposes and optimizes a cooperative non-orthogonal multiple-access (Co-NOMA) scheme in the context of multicell visible light communications (VLC) networks to mitigate inter-cell interference. Consider a network where each access-point (AP) serves two users. In each cell, the weak user (cell-edge user) can be served either directly by the VLC AP, or through the strong user that decodes the weak user message and forwards it through the radio-frequency (RF) link. The paper then considers the problem of maximizing the sum-rate under quality-of-service constraints by allocating the powers of the messages and APs, and determining the links serving each weak user. The paper solves this non-convex problem by first finding closed-form solutions of the users' powers and link selection for fixed APs powers. The APs powers are then iteratively solved in an outer loop. Simulation results show that the proposed scheme improves the sum-rate and fairness as compared to non-orthogonal multiple-access (NOMA) scheme.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".