16-state nonlinear equalizer for IS-54 digital cellular channels
Bibliographic record
Abstract
An evaluation of a number of equalizers for frequency selective fading channels has appeared recently. Linear and decision feedback equalizers have been considered. IS-54 digital cellular channels based on TDM concepts have delay spreads that result in at most one data symbol of overlap. Using a standard fading model, the authors find that a 16-state sequence estimator, following a receive filter matched to the transmitter filter, provides excellent performance for delay spreads from zero to one symbol interval. It is superior to both linear and decision feedback equalizers in this application. Herein is assumed perfect channel state information to establish ultimate performance. In practical application, at most three complex samples of the overall impulse that includes the receiver filter must be estimated. The frequency selective channel is a two-path model with time variation following standard Doppler variations for IS-54 channels. Cochannel interference is included and results are presented for both root-raised-cosine filtered /spl pi//4-DQPSK and QPSK modulation formats.
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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 | 0.002 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".