Movable Access Point-Aided Integrated Visible Light Communication and Sensing Networks
Bibliographic record
Abstract
The emergence of visible light communication (VLC) provides a promising low-cost, radiation-free, and energy-efficient solution to the limited spectrum of wireless networks. However, the design issues of line-of-sight (LOS) blockage, user mobility support, random device orientation, and the limited field-of-view of VLC access points (APs) and receivers have delayed its adoption. This letter explores the use of movable AP (MAP) technology to address these issues in a visible light based joint communication and sensing system. First, a system model for a MAP-aided integrated visible light communication and sensing (IVLCS) network is proposed. Then, a non-convex optimization problem is formulated to maximize the aggregate sum rate and sensing mutual information (MI) by jointly optimizing MAPs’ position and user association. A low-complexity algorithm that obtains a locally optimal solution is proposed by leveraging the difference of convex functions and the majorization-minimization technique. Simulation results reveal that the proposed MAP-aided IVLCS system is more robust against link blockages, provides mobility support and can significantly enhance aggregate sum rate and MI compared to a fixed AP system.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".