Damson HF channel characterisation-a review
Bibliographic record
Abstract
For contemporary HF systems the channel often exhibits low SNR, may well be subject to slow fades and is almost always frequency selective. Until 10 years ago it was common for the high frequency (HF) user to expect low data rates of /spl sim/75 bit/s and low availabilities. However, with the advent of digital signal processing, data rates have increased significantly to 2400 bits/s, 4800 bits/s and beyond in a 3 kHz channel. Such is the progress that commercial digital HF broadcasting is now planned. In order to support these initiatives around 7 years ago the UK, Canada, Norway and Sweden started a programme to characterise the HF channel in a systematic way. This programme is known as DAMSON (Doppler And Multipath Sounding Network). DAMSON experimentation has concentrated on auroral and sub-auroral paths but has also included measurements at mid- and equatorial latitudes. Most of these measurements have concentrated on 3 kHz channels but recently 12 kHz channels, more applicable to digital HF broadcasting applications, have also been assessed. This paper reviews both the system that was developed to make these measurements and the various contributions that have been made to the understanding of the channel and the design of HF modems.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".