Decision-Feedback Detection for Free-Space Optical Communications
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Free-space optics (FSO) have received increased attention recently for last-mile wireless links. In this paper, we investigate noncoherent detection, i.e. detection assuming the absence of channel state information at the receiver, of on-off keying (OOK) in an FSO system. To partially recover the performance loss associated with conventional symbol-by- symbol noncoherent detection, we consider the application of decision-feedback detection (DFD), in which symbol-by-symbol decisions are made using previous decisions and an observation window of N received statistics. Analytical and simulation results indicate that the performance of a DFD receiver approaches the coherent detection lower bound with increasing window length. Consequently, as the proposed receiver exhibits a complexity independent of N, the conclusion is reached that DFD is an effective approach for noncoherent detection in an FSO system.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it