Bibliographic record
Abstract
A new receiver based on decision feedback and linear prediction principles is proposed for the coherent detection of PSK signals in fading channel. This receiver uses the previously detected symbols to estimate the previous channel gains and then uses these estimated channel gains to predict the channel gain continuously, and therefore makes the optimal coherent detection of DPSK. The receiver has a simple structure and can be implemented easily. Simulations of the bit error (BER) performance of QDPSK with the new receiver in both additive white Gaussian noise (AWGN) and Rayleigh flat-fading channels are given. The results show that the proposed receiver provides almost the same BER performance as the ideal coherent receiver in an AWGN channel, is very robust against large carrier frequency offset between the transmitter and receiver, and can provide a reasonably good BER performance in a fast Rayleigh fading channel. Moreover, the fact that the receiver is "blind" leads to a simpler implementation, since there is no need to estimate the fading parameters.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
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".