Dynamic spot diffusing configuration for indoor optical wireless access
Bibliographic record
Abstract
This paper introduces the dynamic spot diffusing (DSD) configuration for high-speed indoor wireless optical communications. In this configuration, data are modulated onto a moving spot which is translated over the ceiling. A multi-element imaging receiver is pointed upward and acquires data whenever the transmitter spot is in its field-of-view (FOV). We develop expressions for the channel capacity of such DSD links and discuss design techniques to maximize these information theoretic bounds. Rather than tracking the transmitter spot, we apply rateless erasure correcting codes to approach the capacity of the simulated DSD links. This technique is demonstrated to have better flexibility, greater multipath immunity, higher data rates and simpler transmitters than previously defined multi-spot and diffuse architectures. In a 6 x 6 x 3 m room, simulated data rates vary between 7 Mbps to 25 Mbps at different positions using a single 100 Mbps transmitter and between 35 Mbps to 84 Mbps using 6 spots and the designed erasure correction code. Using power efficient modulation and power gain due to the spot motion of the DSD system, proportionally higher rates are estimated when faster 1 Gbps and 10 Gbps transmitters are employed.
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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 | 0.000 |
| 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 | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".