Optical domain demultiplexing of subcarrier multiplexed cellular and wireless LAN radio signals
Bibliographic record
Abstract
Subcarrier multiplexed transmission of cellular (900 MHz), personal communications systems (1.8 GHz) and wireless LAN (2.4 GHz) over the fiber has interesting applications. These multi channel radio over fiber links can connect enhanced wireless hot-spots that will support high speed wireless LAN services or low speed cellular services to different customers from the same antenna. Optical pre-filtering of SCM signals allows the use of inexpensive photodetector and increases network flexibility with fiber based optical filters. However, realizing optical demultiplexing at such low frequencies necessitates optical filters with high selectivity and low insertion loss. In this paper, we implemented a fiber wireless access system, where demultiplexing of subcarrier multiplexed cellular and WLAN signals was demonstrated in optical domain using a sub-picometer bandpass filter. Our novel fiber Bragg grating based bandpass filter has a bandwidth of 120 MHz at -3dB, 360 MHz at -10 dB and 1.5 GHz at -20 dB respectively. We experimentally verified that this filter could adequately isolate signals at as low as 900 MHz from 2.4 GHz. Experimental results show that the designed all optical demultiplexer provides about 25 dB isolation between 900 MHz and 2.4 GHz radio signals.
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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".