Non-orthogonal multiple-access-based visible light communications for smart city applications
Why this work is in the frame
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Bibliographic record
Abstract
In this chapter, we provide an overview of non-orthogonal multiple access (NOMA)based visible light communication (VLC) techniques to ensure high data rates, reliable seamless connectivity and improved capacity for a connected smart city. Smart cities utilize information and communication technology (ICT) to monitor, analyze and manage the assets and resources as efficient as possible. With the advent of the Internet of Things (IoT) as an integral part of smart cities, the communication system of the smart city must provide improved quality of service (QoS) with high data rates. VLC is a promising technology to enhance the communication system of a smart city which enables high-speed data transmission simultaneously with illumination. The ability of integrating VLC in device-to-device (D2D) communication, motion detection and localization made it suit for indoor communication in the context of industrial 4.0. Also, VLC can be utilized in vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications that are the key enabling technological components of intelligent transportation system (ITS). To provide a reliable multiple network access technique for the proposed VLC system, NOMA can be used. In addition to the spectral efficiency gain of NOMA, the research indicated that NOMA can effectively support massive connectivity which is paramount in smart city communication systems.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 it