Receiver design for asymmetrically clipped optical OFDM
Why this work is in the frame
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Bibliographic record
Abstract
Asymmetrically clipped optical OFDM (ACO-OFDM) is compatible with optical intensity modulation and is well suited to bandlimited optical wireless channels. By carefully locating data on odd subcarriers and clipping the resulting time signal, ACO-OFDM guarantees non-negative output amplitudes and clipping noise orthogonal to the information. However, in the conventional receiver, clipping noise is ignored in detection and data are extracted from odd subcarriers only. In this paper, a new receiver design for ACO-OFDM is proposed which exploits the structure of the clipping noise to improve the optical power efficiency. By observing the anti-symmetry of time domain samples, a simple pairwise maximum likelihood detector is developed and is used to fix half of the received samples to zero. Simulation results show that employing the proposed detector design leads to 1.3 dB optical gain at a BER of 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-5</sup> .
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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