Analog interference cancellation for full-duplex broadband power line communications
Bibliographic record
Abstract
In this paper, we present an all-analog echo cancellation solution to achieve in-band full-duplex (IBFD) operation in broadband power line communications (BB-PLC). The performance of active digital interference cancellation, as proposed previously for IBFD BB-PLC, is limited by distortion and quantization noise introduced by the analog-to-digital converter (ADC). Hence, we explore analog interference cancellation (AIC) solutions to reduce the power of the signal entering the ADC. We consider various AIC solutions for other communication media known from the literature, and show that a direct implementation of any of these solutions to a BB-PLC system renders an expensive and/or ineffective realization. Acknowledging the specific challenges encountered in BB-PLC, we propose an AIC mechanism that not only eliminates the effects of ADC distortion and quantization noise, but also provides sufficient echo cancellation gain (ECG) to function without an active digital interference cancellation module. We demonstrate through simulation results that our proposed solution provides over 80 dB of ECG, which is sufficient to reduce the echo power down to the minimum power line noise floor.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".