Robust Narrowband Interference Rejection for Power-Line Communication Systems Using IS-OFDM
Bibliographic record
Abstract
In this paper, two narrowband-interference (NBI) rejection methods are formulated for power-line orthogonal frequency-division multiplexing (OFDM) communications. The inherent NBI suppression capability of the OFDM system is improved upon through the application of a spreading sequence (i.e., IS-OFDM) and further improved through the utilization of NBI filtering implemented at the OFDM receiver. A block least-mean-square (BLMS) algorithm, called cyclic prefix BLMS (CP-BLMS), is constructed for time-domain NBI filtering and a corresponding fast BLMS (FBLMS) algorithm, called linear FBLMS (LFBLMS), is also presented which performs the NBI filtering in the frequency domain. The fast implementation reduces the computational burden of the additional filtering process for a large number of subcarriers without impact on filter performance. Both simulation and theoretical analysis demonstrate the bit-error rate improvement of the proposed approaches compared to previous methods. Numerical results from theoretical analysis also illustrate the speed advantage of the LFBLMS algorithm.
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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".