Matrix- and Tensor-Based RFI Detectors for Multi-Antenna Wireless Communications
Bibliographic record
Abstract
Radio frequency interference (RFI) is affecting various radio frequency operating systems. Mentioning of practical wireless channels, meanwhile, RFI can be received through a multi-path fading channel. In such scenarios, robust detection of RFI can be challenging since the signal of interest can also be received through a multi-path fading channel. To this end, by introducing a tensor-based hypothesis testing framework, this paper proposes a matrix-based RFI detector (MB-RD) and a tensor-based RFI detector (TB-RD) for RFI received through a multi-path fading channel. Simulation results demonstrate that TB-RD outperforms-especially for a weak RFI-MB-RD and the generalized likelihood ratio test (GLRT) detector whenever the number of receiving antennas increases.
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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 | 0.000 | 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 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".