Channel Estimation, Equalization andPhaseCorrection forSingle Carrier Underwater Acoustic Communications
Bibliographic record
Abstract
Inthispaper, we employa time-domain channel estimation, equalization andphasecorrection schemeforsingle carrier single input multiple output (SIMO)underwater acoustic communications. Inthis scheme, Doppler shift, whichiscaused byrelative motion between transducer (source) andhydrophones (receiver), isestimated andcompensated inthereceived baseband signals. Thenthechannel isestimated usinga smalltraining blockatthefront ofatransmitted datapackage, inwhichthe dataisartificially partitioned intoconsecutive datablocks. The estimated channel isutilized toequalize a blockofreceived data, thentheequalized dataisprocessed byagroup-wise phase correction before datadetection. Attheendofthedetected data block, asmallportion ofthedetected dataisutilized toupdate channel estimation, andthere-estimated channel isemployed for channel equalization fornextdatablock. Thisblock-wise channel estimation, equalization andphasecorrection process isrepeated until theentire datapackage isprocessed. Thereceiver scheme istested withexperimental datameasured atSaint Margaret's Bay,NovaScotia, Canada, inMay2006. Theresults showthat itcanbeapplied notonlytothescenario offixed source tofixed receiver, butalsotothemoving source tofixed receiver case. The achievable uncoded biterror rate(BER)isontheorderof10-4 formoving-to-fixed transmissions, andontheorderof10-5for fixed-to-fixed transmissions.
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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 | 0.000 | 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".