A Nonlinear Transmission Line Technique for Generating Efficient and Low-Ringing Picosecond Pulses for Ultrabroadband and Ultrafast Systems
Bibliographic record
Abstract
This paper presents a nonlinear transmission line (NLTL)-based scheme to develop an efficient and low-ringing picosecond pulse generator for ultrabroadband and ultrafast system applications. The proposed NLTL scheme stems from a unique combination of single varactor diode and stacked varactor diode per NLTL cell, which is designed to exploit a significant effect of non-linearity in connection with the varactor diode. This technique generates a higher compression factor in both rise and fall time of NLTL circuits in comparison to single varactor diodes per NLTL section. This scheme is validated to work well in a triple-stacked NLTL topology by maximizing the compression factor. Two pulse generators are then developed based on the proposed concept, where a mixed SRD topology is used for gaussian pulse generation and integrated with a triple-stacked NLTL. This achieves shorter pulse durations and a higher compression capability. The use of NLTLs with triple-stacked varactor diodes in a cell is also explored theoretically and is shown to maximize the compression capability by effectively increasing the punch through, turn-on, and break down voltages. Theoretical development and simulation of two triple-stacked NLTLs based on the rise and fall time-compression are provided, and final experimental prototypes for pulse generators are fabricated and measured. It is found from measurements that the full-width half maximum (FWHM) of the rise time-compression-based pulse generator is almost 15.78ps with a ringing level of -11.29dB, while the FWHM of the fall time-compression-based pulse generator is almost 17ps with a ringing level of -8.43dB. Finally, these pulse generators are compared with the current states of the art in terms of the implemented scheme, pulse duration, FWHM, pulse shapes, and detailed ringing level. The reconfigurable capability of the pulse generators is also briefly explored, and it is shown that the proposed pulse generators can easily be reconfigured between gaussian and monocycle pulse shapes. The power spectrum of the proposed pulse generators is also presented. It is found that they are well suitable for ultra-broadband and ultrafast systems, such as Impulse Radar Ultrawideband (IR-UWB) applications, due to higher pulse compression capability, ease of integration, flexible pulse tunability, and modification to higher order gaussian waveforms.
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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 | 0.000 |
| 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 | 0.001 |
| Open science | 0.001 | 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".