Digitally Controlled Analog Cancellation for Full Duplex Broadband Power Line Communications
Bibliographic record
Abstract
Although in-band full-duplexing (IBFD) has long been implemented in various communication media, it was only recently that an IBFD solution was presented for broadband power line communications (BB-PLCs). The maximum attainable echo suppression using this solution is, however, limited by the dynamic range of the analog-to-digital converter (ADC). To counter this critical constraint, we propose echo cancellation in the analog domain, while persisting with a low-complexity frequency domain digital echo estimation. By formulating an expression for the number of ADC bits lost in IBFD over a conventional half-duplex operation, we show that the ADC dynamic range is no longer a limiting factor for our solution. We further extend our solution to present an analog cancellation method for multiple-input multiple-output IBFD BB-PLC systems. Finally, we present simulation results of echo cancellation and data rate gains obtained under realistic in-home BB-PLC settings, to demonstrate that our solution is capable of doubling bidirectional transfer rates in a large number of the tested network conditions.
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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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".