Effect of encoder–decoder mismatch due to wavelength and time misalignments on the performance of two-dimensional wavelength–time optical code-division multiple access systems
Bibliographic record
Abstract
We examine the effects of encoder and decoder mismatch due to wavelength and time chip misalignments on the bit-error rate (BER) performance of two-dimensional (2D) wavelength--time optical code-division multiple access systems. We investigate several instances of misalignment in the desired user encoder and decoder as well as in the interfering user encoders. Our simulation methodology can be used to analyze any type of 2D wavelength--time code family as well as probability distribution for misalignment. For illustration purposes, we consider codes generated by use of the depth-first search algorithm and a Gaussian distribution for the misalignment. Our simulation results show that, in the case of a misalignment in either wavelength or time chip, the variance of the distribution for the misalignment must be below 0.01 for the corresponding degradation in the BER system's performance to be less than 1 order of magnitude compared with that when there is no mismatch between the encoders and decoders. The tolerances become even more strict when misalignments in both wavelength and time chips are considered. Furthermore, our results show that the effect of misalignment in wavelength (time chips) is the same regardless of the number of wavelengths (time chips) used in the codes.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".