Decision Aided detection and performance of Continuous Phase Chirp Keying
Bibliographic record
Abstract
A Decision Aided Receiver (DAR) for coherent detection of Continuous Phase Chirp Keying (CPCK) in Additive White Gaussian Noise (AWGN) is presented. The structure of DAR is generic and applies to arbitrary Continuous Phase Modulation (CPM). The receiver complexity is a linear function of number of observed symbol intervals and uses repeated processing of received waveform at the receiver. Performance analysis of DAR is presented and easy-to-compute closed-form analytical expressions for Bit Error Rate (BER) have been obtained for CPCK. The DAR is attractive by virtue of its superior error performance and low-complexity relative to the Average Matched Filter (AMF) receiver for CPCK, especially for a wide range of CPCK modulation parameters and decision observation lengths. For example, it is shown that 2-bit DAR can outperform 2-bit AMF receiver for CPCK with modulation parameters (q, w) = (0.98, 4.15).
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".