Frequency-domain estimation of time-domain correlation matrix for MIMO-OFDM systems
Why this work is in the frame
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Bibliographic record
Abstract
Since the received MIMO-OFDM signal is usually corrupted in the time-domain due to some adverse factors such as frequency offset and large peak-to-average power ratio (PAPR) etc., a high-quality signal may only be obtained in the frequency domain. However, the second-order statistics of the time-domain signal are very often used in a blind or semi-blind channel estimation, which means that an IFFT processor is required in the receiver to achieve the time-domain signal. This additional IFFT incurs a high computational complexity and a long time delay in real-time communication systems. In this paper, we propose a new algorithm for the computation of the time-domain correlation matrix directly from the received frequency-domain signal. The proposed algorithm is proven to be equivalent to the original algorithm of estimating the time-domain correlation matrix, while the former can avoid an IFFT process when high-quality signal is only available in the frequency domain.
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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