2×1-D fast Fourier transform interpolation for LTE-A OFDM pilot-based channel estimation
Bibliographic record
Abstract
In this paper, we investigate an interpolation technique for pilot-symbol assisted channel estimation in Long Term Evolution-Advanced (LTE-A) Orthogonal Frequency Division Multiplexing (OFDM). The studied interpolation method is a two one-dimensional (2 × 1-D) Fast Fourier Transform (FFT) interpolator. The performance of such interpolator in estimating LTE-A Cell-specific Reference Signals (C-RS) is reported and compared to different variations of Wiener and moving average filters, with different interpolation techniques. Moreover, degradation in LTE-A OFDM performance for high mobility channels is presented and discussed. It is shown that Wiener/2 × 1-D FFT/IFFT as a full system does not require setting a window size and provides better performance compared to Equal Weight Averaging (EWA)/Spline variations.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".