Frequency domain equalization for high data rate multipath channels
Why this work is in the frame
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Bibliographic record
Abstract
High data rate transmission over multipath channels requires equalizers of long impulse response. In such cases, frequency domain implementation of the block least mean square (BLMS) algorithm offers low complexity growth relative to time domain techniques. The work presented herein is devoted to a study of the fast BLMS (FBLMS) algorithm implemented in the frequency domain using overlap-save sectioning and the fast Fourier transform (FFT). We examine the bit error rate (BER) performance for high data rate quadrature phase shift keying (QPSK) transmission over a multipath channel as well as the computational complexity of the FBLMS equalizer in comparison to the time domain implementation. Finally, we show how normalizing the step size of the FBLMS algorithm according to the power distribution of the input process results in a significant improvement in the equalizer convergence relative to the time domain methods.
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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 | 0.000 | 0.000 |
| 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