Absolute Value Layered ACO-OFDM for Intensity-Modulated Optical Wireless Channels
Why this work is in the frame
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Bibliographic record
Abstract
Enhanced unipolar orthogonal frequency division multiplexing (eU-OFDM) and layered asymmetrically clipped optical OFDM (LACO-OFDM) are spectrally efficient modulation techniques for intensity modulated systems which layer multiple non-negative signals. In this paper, we propose absolute value layered asymmetrically clipped optical OFDM (ALACO-OFDM), which further improves the spectral efficiency while using a smaller number of layers and no explicit direct current (DC) bias. In ALACO-OFDM, asymmetrically clipped optical OFDM (ACO-OFDM) signals are sent at the first L layers and absolute value optical OFDM (AVO-OFDM) is used for the remaining subcarriers and transmitted simultaneously. Analysis indicates that ALACO- achieves higher spectral efficiency than eU- or LACO-OFDM while using a smaller number of layers. Bounds on achievable information rates of ALACO-OFDM and related layered ACO-OFDM techniques are also developed. Two optical power allocation schemes over the layers of ALACO-OFDM are developed with the objective of optimizing uncoded transmission performance and the achievable information rate respectively. Additionally, a theoretical bound on the uncoded BER of ALACO-OFDM is derived. Monte Carlo simulation results indicate ALACO-OFDM with the optimum power allocation achieves significant uncoded BER performance gains compared to its counterparts at the same spectral efficiency while having a smaller peak-to-average power ratio.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 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