Bibliographic record
Abstract
A 71-76GHz millimeter-wave filter is designed and implemented in a multilayer LTCC module to help attenuate the side spur signal level.The filter is aimed to be embedded in a novel E-band architecture designed at Huawei for millimeter-wave signal communication application.The goal of the filter is to help reduce the third harmonic and fourth harmonic leakage of the LO signal from tripler into the RF channel.Through measurement, for -15dBm received signal power, the 3 rd and 4 th harmonic leakage levels sof the LO signal is around -25dBc, and both of their frequency range are very close to the transmission band.The designed bandpass filter attenuates the 3 rd and 4 th harmonic signal power down to -50dBc with a low filter order and small physical size.Unfortunately, access to the fabricated filter was not possible due to existing political tension between the US government and Huawei.The fabricated filter was not shipped to Ottawa, and as a result, it was not measured.A second bandpass filter operating at 10GHz is fabricated using Rogers4360 substrate for measurement and validation.The measurement results show some deviations with simulation results.The center frequency shifts from 10GHz to 11.25GHz.Through analysis, the milling depth of the fabrication process affects the measurement result.In our test, a 0.243mm milling depth causes the filter center frequency shift to 11.25GHz.
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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".