Adaptive equalization and diversity combining for a mobile radio channel
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The feasibility of a digital cellular radio (DCR) system which uses a jointly adaptive decision-feedback equalizer and diversity combiner is discussed. The current estimates of the channel impulse response (CIR) are utilized at each diversity branch to compute the receiver parameters periodically. A block-adaptive strategy that computes the time-varying CIR by interpolating a set of CIR estimates obtained through periodic training is proposed. Despite incurring some inherent processing delay and throughput reduction, this interpolation strategy is shown to have the advantage of immunity to decision errors which would quite likely occur during a deep fade. It is shown that the system performance is limited mainly by the CIR estimation caused by imperfect training which is manifest in the form of an irreducible bit error rate at high signal-to-noise ratios (SNRs).< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
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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 | 0.001 | 0.001 |
| 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 it