Miniaturized, Lumped-Element Filters for Customized System-on-Package L-Band Receivers
Bibliographic record
Abstract
The system-on-package (SoP) approach to design wireless front ends has proven to optimize the tradeoff between performance and size. In this paper, two new and highly compact bandpass filters are presented that show the greatest degree of miniaturization of any bandpass filters presented to date when their volume is measured in guided wavelengths. A novel packaging technique where most of the filter components are folded beneath the resonator inductors allows for this level of miniaturization. The filters are designed as lumped-element equivalent circuits and fabricated in standard low-permittivity low-temperature cofired ceramic technology that makes them suitable for embedding within a mass-producible SoP solution. In addition, electric and magnetic couplings are used to create finite transmission zeros that enhance the selectivity of these filters. The second-order filter demonstrates an insertion loss of 2.2 dB and a 3-dB bandwidth of 11% at a center frequency of 1.524 GHz. Meanwhile, the fourth-order implementation shows an insertion loss of 4.92 dB and a 3-dB bandwidth of 6.6% at a center frequency of 1.521 GHz. In both cases, the agreement between simulations and measurements is excellent. Careful analysis of individual capacitors and inductors comprising the filters is provided to explain the link between process parameters and actual measured performances.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".