A two-dimensional signal space for bandlimited optical intensity channels
Bibliographic record
Abstract
Bandlimited optical intensity channels, such as visible light communication (VLC) systems, require that all signals satisfy a bandwidth constraint as well as average and non-negativity amplitude constraints. In this paper, a two-dimensional signal space for optical intensity channels is presented in which all signals are strictly bandlimited. A novel feature of this model is that the strict non-negativity constraint is relaxed and the signal space parameterizes the probability that the resulting output amplitude is negative. The motivation for this relaxation is that even though the optical intensity channel only supports non-negative amplitudes, if the likelihood of a negative amplitude excursion is small enough the impact of clipping or biasing on system performance will be negligible. For a given signal space, the probability that the output signal assumes a negative amplitude is rigorously upperbounded and also numerically found with a tractable and tight approximation. The uncoded power and spectral efficiencies are computed for two-dimensional hexagonal lattice constellations. For a given optical power, constellations developed with the new signal space have larger spectral efficiencies over M-PAM using the minimum bandwidth optical intensity Nyquist pulse.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".