Study on Multi-Hypothesis Decision Feedback Equalization for DS/SS-CDMA Underwater Acoustic Communication
Bibliographic record
Abstract
A study of chi Prate multi-hypothesis decision feedback equalization algorithm for DS/SS-CDMA underwater acoustic communication is presented.Underwater acoustic communication channel is a delay-Doppler double spreading channel.Fading and Doppler spreading severely degrade the correlation characteristic of the spread spectrum signals,so Doppler shift compensation and equalization are needed before decoding.By applying Space diversity-Doppler compensation-Fast Self-Optimized adaptive decision feedback equalization algorithm into DS/SS-CDMA communication,a chi Prate multi-hypothesis adaptive decision feedback equalization algorithm for DS/SS-CDMA underwater acoustic communication is proposed and its performance is analyzed with real sea-trial data.At the price of computational complexity,the algorithm dramatically improves DS/SS-CDMA communication quality.Very low bit error rate is achieved under fast changing multi-path and Doppler shift condition,and the equalizer is stable under low SNR.The overall performance of this algorithm is a satisfactory.
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How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".