Low distortion transmission of 802.11a/n signals in amplified radio over fibre links with modulator bias optimization
Bibliographic record
Abstract
In this work, we study the propagation of an IEEE 802.11a/n compliant signal over an analog optical link employing a Mach-Zehnder modulator, an Erbium doped fibre amplifier and 10 km of standard fibre. We show that, when the bias of the modulator is controlled in order to maximize the received RF power at the end of the link, the link linearity can also be improved. This is due to the interaction between the distortion caused by the Mach-Zehnder and the fibre nonlinearities. We simulate and measure the link intermodulation distortion (ID3) as a function of the modulator bias, showing in which condi-tions it is possible to simultaneously minimize the ID3 and maximize the link gain. Also, we show that the error vector magnitude, an important quality factor of OFDM IEEE 802.11a/n signals, can greatly benefit from the im-proved link linearity. Thus, the bias optimization allows for both higher power and higher quality transmission with respect to standard quadrature biased links. KEY WORDS ROF links, wireless signals on optical link, fibre nonlin-earities, Mach-Zehnder nonlinearities.
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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 | 0.001 |
| 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 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".