On the robustness of oversampled filter bank multi carrier systems against frequency offset
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Bibliographic record
Abstract
In this paper, we study the effect of oversampling in a perfect reconstruction (PR) filter bank multi carrier (FBMC) system recently proposed by the authors. Particularly, we investigate the performance of this system in the presence of carrier frequency offset (CFO). We show that the CFO introduces interference components in the receiver. By exploiting the statistical properties of the received subband signals, the average of the signal-to-interference ratio (SIR) is derived to exhibit the tradeoff between performance and efficiency. Furthermore, bit-error-rate (BER) comparisons of FBMC systems with different oversampling ratios over frequency-selective and additive white Gaussian noise (AWGN) channels in the presence of CFO are presented. These results confirm that oversampling increases robustness of the system against CFO.
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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) | 0.001 | 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 it