A Companding Technique to Reduce Peak-to-Average Ratio in Discrete Multitone Wireline Receivers
Bibliographic record
Abstract
Multicarrier modulation, while providing a theoretical pathway to data rates approaching the Shannon limit and being extensively utilized in wireless communication, has encountered limited application in high-speed wireline communication. This limitation is primarily due to substantial large amplitude peaks, which necessitates a reduction in the signal’s power levels to circumvent signal clipping. This, in turn, results in a low signal-to-noise ratio (SNR) which puts these modulations at a serious disadvantage compared to conventional modulation schemes. This work proposes a novel companding solution in the design of the Continuous Time Linear Equalizer (CTLE) alongside nonlinear blocks to reduce Peak to Average Power Ratio (PAPR), therefore improving the overall link performance. This paper presents a PAPR reduction technique and its implementation in the receiver, distinguishing it from previous studies that place the compander at the transmitter where it fails to work in the presence of an Inter-Symbol Interference (ISI) channel. A theoretical study as well as an implementation of this method is provided, and the merits and performance improvements are demonstrated.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".