Evaluation of transmission alternatives for the return cable band
Bibliographic record
Abstract
This research concerns comparing the performance of various transmission and reception alternatives for the 5-45 MHz portion of the upstream path of the return coaxial cable band. This evaluation is based on ingress noise spectra files collected over an extended period of time from various sites. This data has been used to evaluate the return band capacity as a function of sub-channel bandwidth in FDMA and TDMA/FDMA schemes. In addition, the time varying aspect of the channel is considered using variable bit rate allocation to sub-bands, as in OFDM with frequency division multiplexing. Furthermore, the same analysis is repeated for a wideband system using a decision feedback equalizer (WDFE) contending with ingress noise instead of channel distortion. This research demonstrates that using a variable channel allocation (VCA) scheme to match the time varying aspect of the channel enhances the performance over a fixed channel allocation (FCA) scheme. It also shows that a wideband system using an adaptive decision feedback equalizer (DFE) performs similar to a multi-carrier modulation (MCM) method, and that reasonable performance can be obtained by using a system of lower complexity consisting of the combination of the FCA with the WDFE.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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 | 0.000 |
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".