Characteristics and performance of various VDSL RFI suppression techniques
Bibliographic record
Abstract
The past few years have seen ADSL widely deployed as the telephone companies attempted to grow their market share in the consumer service industry of high speed internet access. Bundling a digital video service offering together with data and phone services is seen by many telephone companies as the next step for protecting, if not growing, their market share. VDSL is one technology that promises to provide the required rates over existing twisted pairs for supporting these services. VDSL employs the frequency band spanning from 25 kHz to 12 MHz, a significantly larger band than used by ADSL. As a consequence, the VDSL band is adjacent to or overlaps with other radio signalling bands such as Amateur Radio (HAM) and AM broadcasts. These signals may introduce radio frequency interference (RFT) in VDSL signals, which will degrade VDSL performance. Many approaches can be found in the literature for reducing the impact of RFI on VDSL communication. These methods however may not always be as practical or efficient as predicted when applied to real systems adhering to a common standard. This thesis attempts to quantify the impact of RFI on typical multi-carrier modulation (MCM) basedVDSL systems, also known as discrete multi-tone (DMT) VDSL, and researches some of the most promising suppression techniques for mitigating the effect of RFI in such systems. Elaborate end-to-end simulations are carried out to investigate the effect of these suppression techniques on system performance, both with and without RFI present. The thesis concludes by highlighting the performance and complexity characteristics of the various RFI suppression techniques considered.
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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".