A High Spectral Efficiency Coherent RoF System Based on OSSB Modulation With Low-Cost Free-Running Laser Sources for UDWDM-PONs
Bibliographic record
Abstract
A coherent radio over fiber (RoF) system based on optical single-sideband modulation with no optical carrier (OSSB) for ultradense wavelength division multiplexing passive optical networks (UDWDM-PONs) is proposed and experimentally demonstrated. For one channel of the UDWDM-PONs, at the transmitter, the OSSB RoF signal is generated using a dual parallel Mach-Zehnder modulator (DP-MZM) with a real-valued precoded microwave vector signal which is applied to the DP-MZM via the two electrodes with one having a 90° phase shift. Then, the OSSB RoF signal is sent to a coherent receiver over a single-mode fiber (SMF). The coherent receiver with a free-running laser source as a local oscillator (LO) is used to perform the coherent detection. To recover the standard microwave vector signals from the real-valued precoded microwave vector signal that is embedded in a strong phase noise introduced by both the transmitter laser source and the LO laser source, a digital signal processing algorithm is developed to perform phase noise cancellation. An experiment is performed. The transmission of a 1.25-Gbps quadrature phase shift keying, a 1.875-Gbps eight-phase shift keying (8-PSK), and a 2.5-Gbps 16 quadrature amplitude modulation (16-QAM) microwave vector signals with a channel spacing as narrow as 3 GHz over a 25-km SMF is experimentally demonstrated. For the transmission of the 2.5-Gbps 16-QAM microwave vector signal, the received optical sensitivity at forward error correction level over a 25-km SMF link is -24.8 dBm, while for the 1.875-Gbps 8-PSK microwave vector signal, it can reach -29.8 dBm which leaves an enough margin to accommodate the splitting losses in the optical distribution networks.
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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 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".