Fractionally spaced equalization for analog cellular data modems
Bibliographic record
Abstract
The authors consider a simple add-on system to analog cellular radios to offer 9600 b/s data services. The feasibility of using a fractionally spaced equalizer with a burst noise detector is considered. The authors examine equalization performance for subcarrier-based quadrature amplitude modulation (QAM). The performance of a T/4 and a T/2 spaced equalizer is compared with the performance of a symbol spaced equalizer for low to medium signal-to-noise ratios (SNRs). Performance criteria are minimum mean square error, timing sensitivity, SNR after equalization, signal-to-interference ratio (SIR) after equalization, and peak distortion (PD) after equalization. By means of simulation the convergence aspects of the T/2 spaced equalizer were investigated after differing burst and correlated noise scenarios. A noise detection plus equalizer control scheme is proposed and evaluated to maintain operation of the equalizer under burst noise conditions.>
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".