Investigation of 340-Gbps terrestrial FSO link incorporating spectral-efficient DP-QPSK-PolSK hybrid modulation scheme
Bibliographic record
Abstract
A high-capacity spectral-efficient dual-polarization quadrature phase-shift keying (DP-QPSK)-polarization shift-keying (PolSK) hybrid modulation scheme for terrestrial free-space optics (FSO) transmission link is proposed and investigated. A DP-QPSK signal modulated at 300 Gbps and a PolSK signal modulated at 40 Gbps are simultaneously transmitted using a single optical carrier over the FSO link. The proposed link performance is investigated under different weather conditions, where the bit error rate metric is used to evaluate the performance of the PolSK modulated signal and the error vector magnitude parameter is used for the DP-QPSK signal. The FSO link range and the required received power are carefully explored. The conducted numerical simulations of the proposed system showed reliable 340-Gbps data transmission over link ranges varying from 1.6125 to 50 km depending on the weather conditions. The impact of the channel scintillation due to atmospheric turbulence is also investigated. The proposed high-speed FSO transmission system offers a promising solution for high-bandwidth hungry systems used for the internet of things, 5G, and smart cities. It can also be used in developing fronthaul/backhaul links for future wireless networks and optical access networks. The performance of the proposed transmission system is compared with recently published work in the literature.
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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) | 0.001 | 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".