Diversity Reception for Deep-Space Optical Communication Using Linear Projections
Bibliographic record
Abstract
A novel spatial diversity receiver for deep-space optical communication links is proposed. Using digital micromirror devices, the receiver optically computes linear projections of the turbulence-degraded focal-plane signal distribution onto an orthogonal binary basis. By using such projections, an estimate of the signal distribution is computed and updated adaptively to follow the time variations of the signal distribution. The estimate is used to perform selection combining, i.e., to select the portions of the focal plane that contain significant energy for symbol detection. The proposed receiver is less complex, requires less high-speed analog electronics and has lower preamplifier noise than a comparable multiple-detector array receiver. On the other hand, the proposed receiver requires more optical components and additional digital hardware to control the micromirror devices. Symbol error-rates (SERs) are simulated on a photon-counting channel and performance improvements about 2-5 optical decibels (dBo) over a conventional single-detector receiver are obtained at SER = 10-2.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".