Efficient Sequential Blind Beamforming for Wireless Underground Communications
Why this work is in the frame
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Bibliographic record
Abstract
In this paper, a new technique enabling path diversity maximum ratio combining (MRC) is proposed to leverage the performance of the previously proposed Sequential Blind Beamforming (SBB) method. The latter mitigates the inter-symbol and intra-symbol interferences and recovers the signal and its integer and non-integer (fractional) multiple replicas using jointly CMA, LMS and adaptive fractional time delay estimation. While implementing EGC at the combining step can give an acceptable performance in the SBB, since the resolved paths have common phase ambiguity, more substantial improvement can be obtained by implementing coherent MRC with hard decision feedback identification. Simulations results in different scenarios validate the superiority of the SBB using the proposed MRC compared to the EGC path combiner.
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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 | 0.001 | 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 it