Inter-signal timing skew compensation of parallel links with current-mode incremental signalling
Bibliographic record
Abstract
This study proposes a new inter-signal timing skew compensation technique for parallel links with current-mode incremental signalling. The maximum deskew range is one bit time in both directions. Both the transmitters and receivers of the links are current-mode configured to take the advantages of current-mode signalling. Each receiver maps the direction of its channel current representing the logic state of the incoming data to two voltages of different values, enabling a convenient recovery of both the logic state and timing information of the received data. The feedback at the front-end of the receiver minimises the dependence of the input impedance of the receiver on the direction of the channel current so that data-dependent impedance mismatch is minimised. Inter-signal timing skews are compensated by inserting a delay line in each channel whose time delay is determined by the phase difference between the master sampling clock and data. A voltage replication circuit is proposed to copy the obtained optimal control voltage of the delay line of each channel so that the optimal deskew control voltage of the delay line is sustained. To assess the effectiveness of the proposed inter-signal timing skew compensation technique, a 2-bit 1 Gbytes/s parallel link has been implemented in UMC-0.13 µm 1.2 V CMOS technology and analysed using SpectreRF with BSIM3V3 device models. Simulation results demonstrate that the proposed inter-signal timing skew compensation method can compensate inter-signal timing skew up to one bit time in both directions.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".