Semiblind Sparse Channel Estimation for MIMO-OFDM Systems
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Bibliographic record
Abstract
In this paper, a semiblind algorithm is presented for the estimation of sparse multiple-input-multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) channels. An analysis of the second-order statistics of the signal that was received through a sparse MIMO channel is first conducted, showing that the correlation matrices of the received signal can be expressed in terms of the most significant taps (MSTs) of the sparse channel. This relationship is used to derive a blind constraint for the effective channel vector that corresponds to the MST position. The blind constraint is then combined with the training-based least square criterion to develop a semiblind approach for the estimation of MSTs of the sparse channel. A signal perturbation analysis of the proposed approach is conducted, showing that the new semiblind solution is not subject to the signal perturbation error when the sparse channel is a decimated version of a full finite impulse response channel. Furthermore, the proposed sparse semiblind algorithm has been extended for the estimation of channels in the upsampling domain for MIMO-OFDM systems with pulse shaping. A number of computer-simulation-based experiments for various sparse channels are carried out to confirm the effectiveness of the proposed semiblind approach.
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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 | 0.001 | 0.001 |
| 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)
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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