Square-Wave Spatial Optical Orthogonal Frequency-Division Multiplexing
Bibliographic record
Abstract
Visible light communication (VLC) systems leverage illumination devices, such as light-emitting diodes (LEDs), to serve a dual role as indoor high-speed communication downlinks. Though high data rates are possible using orthogonal frequency-division (OFDM) in VLC systems, the impact on the complexity and luminous efficacy of the luminaire remain among the key challenges. In this paper,square-wave spatial optical OFDM(SW-SO-OFDM) is proposed which transmits an OFDM signal using$G$square-wave subcarriers from$G$LED groups and allowing them to sum in space. Using a binary-level square-wave carrier signal eliminates the need for digital-to-analog conversion, non-linear pre-distortion hardware and the transmitter inverse Fourier transform, thereby greatly reducing the complexity of the transmitter in the luminaire. Further, by coordinating the binary transmissions from pairs of LED groups, SW-SO-OFDM can transmit multi-level constellations, which further improves the bandwidth efficiency. Through simulation and experiment, SW-SO-OFDM is shown to provide communication performance comparable to SO-OFDM and to significantly outperform conventional DC-biased (DCO)-OFDM at high signal-to-noise ratios, while considerably reducing the overall transmitter complexity in the luminaire.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".