Multiple-symbol detection for photon-counting MIMO 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
We employ a photon-counting signal model of a multiple-input multiple-output (MIMO) free-space optical (FSO) system and investigate detection assuming the absence of channel state information (CSI) at the receiver, in moderate to strong atmospheric turbulence. The considered modulation format is on-off keying with repetition coding across the transmitters. To partially recover the performance loss associated with symbol-by-symbol detection without CSI, we consider the application of multiple-symbol detection (MSD) to equal gain combined (EGC) statistics. We develop a fast search algorithm for EGC-MSD and propose a suboptimal closed-form decision metric suitable for reduced-complexity implementation; performance results confirm that the true and suboptimal metrics perform comparably well. Significantly, the complexity of our receiver, on a per bit-decision basis, is only logarithmically dependent on the observation window length N, and is effectively independent of the size of the MIMO array. We also present the framework for a decision-feedback receiver and obtain performance expressions for the ideal case of error-free feedback; these expressions serve as an upper bound to the performance of EGC-MSD. Analytical and simulation results indicate that the system effectively realizes the diversity gains expected from a MIMO configuration and that the performance of the EGC-MSD receiver approaches the EGC with CSI lower bound with increasing N.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.005 | 0.000 |
| Research integrity | 0.000 | 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