Quantum-Dash Semiconductor Optical Amplifier for Millimeter-Wave over Fibre Wireless Fronthaul Systems
Bibliographic record
Abstract
This paper demonstrates a five-layer InAs/InP quantum-dash semiconductor optical amplifier (QDash-SOA), which will be integrated into microwave-photonic on-chip devices for millimeter-wave (mmWave) over fibre wireless networking systems. A thorough investigation of the QDash-SOA is conducted regarding its communication performance at different temperatures, bias currents, and input powers. The investigation shows a fibre-to-fibre (FtF) small-signal gain of 18.79 dB and a noise figure of 6.3 dB. In a common application with a 300 mA bias current and 25 °C temperature, the peak FtF gain is located at 1507.8 nm, which is 17.68 dB, with 3 dB gain bandwidth of 56.6 nm. Furthermore, the QDash-SOA is verified in a mmWave radio-over-fibre link with QAM (32 Gb/s 64-QAM 4-GBaud) and OFDM (250 MHz 64-QAM) signals. The average error vector magnitude of the QAM and OFDM signals after a 2 m wireless link could be as low as 8.29% and 6.78%, respectively. These findings highlight the QDash-SOA’s potential as a key amplifying component in future integrated microwave-photonic on-chip devices.
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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 | 0.000 |
| 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) | 0.002 | 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".