Quantum dot coherent comb lasers for B5G/6G mobile and terrestrial communication systems
Bibliographic record
Abstract
Future mobile and terrestrial communication systems B5G/6G are strongly expected to heterogeneously realize typically diversified performances, i.e. high-data-rate, high-mobility, low-latency, high-capacity, massive-connectivity and low-energy in order to satisfy the highly diversified application requirements. To achieve those goals the operation band of B5G/6G should be primarily in the millimeter-wave (mmW) range. Generation and distribution of mmW with traditional methods is limited by electronic bottleneck and associated complexity. Consequently broad bandwidth, simple, efficient, and cost-effective photonic mmW-over-fiber (mmWoF) transmission systems are solutions for B5G/6G. The spectral purity of mmW carriers is necessary. Numerous approaches have been proposed to generate pure mmW signals. Compared with other technologies, quantum dash or dot (QD) coherent comb lasers (QD CCLs) have great advantages for mmW generation because QD-CCLs with low power consumption and chip-scale integration capacity with silicon can provide multiple highly correlated and low noise optical channels. In this paper we will present our developed InAs/InP QD-CCLs around 1550 nm with the channel spacing from 10 GHz to 1000 GHz and the output power up to 50 mW. By using a C-band QD CCL and based on the single- and dual-optical carrier modulation schemes, an up to 16-Gb/s mmWoF optical heterodyne wireless signal at 28 GHz through a 25-km single mode fiber before the mmW carrier is optically synthesized remotely for detection over a 2-m free space. The data capacity and performance of the proposed mmWoF link can be significantly increased by utilizing a duplex mmWoF link with MIMO and WDM technique, which provides a cost-efficient and promising solution for Terabit/s capacity mmWoF fronthaul systems of B5G/6G 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".