Bibliographic record
Abstract
Multi-port implementations in Ka-band and V-band receivers for Wireless Local Area Networks (WLANs) dedicated to high data-rate communications are discussed. The multiport interferometer is an innovative approach, due to its intrinsic properties, such as wide bandwidth, reduced local oscillator power required to perform efficient down-conversion, excellent isolation between input RF ports, and very good suppression of harmonic and spurious products. Multi-ports have been successfully used to demodulate various QAM/PSK signals at hundreds of Mb/s data rates. Furthermore, multi-port W-band automotive Continuous Wave (CW), V-band Frequency Modulated CW (FMCW), and Phase Coded CW (PCCW) radar sensors with their related relative velocity and distance measurement principles are discussed and compared. Computed Aided Design (CAD) tools, such as Advanced Design Systems (ADS) of Agilent Technologies and High Frequency Structure Simulator (HFSS) of Ansoft have been used for circuit designs and system simulations. Test bench prototype photographs, and comparative analysis between simulation and measurement results enforce the presentation.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.039 | 0.028 |
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".