Performance of Weak Asymmetric MHPM Signals in Non-Gaussian Noise
Bibliographic record
Abstract
A locally optimum receiver structure is derived for coherent detection of Multi-H phase-coded modulation (MHPM), with asymmetric modulation parameters, signals in non-Gaussian noise. The receiver consists of a memoryless non-linearity, -d/dr ln pN(r), followed by a coherent average matched filter (AMF) for MHPM with asymmetric modulation parameters, where pN(r) denotes the first-order probability density of the noise. The limiting performance estimates of this receiver are derived and expressions for bit error rate (BER) are presented. It is observed that the BER is a function of: i) signal-to-noise ratio S; ii) the number of observation intervals n; iii) signal modulation parameters; and iv) the quantity L referred to as the asymptotic relative efficiency (ARE). Numerical results for BER performance of the locally optimum receiver are presented. Middleton's class A noise models is considered.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".