MMIC and RFIC Solutions for Modern Radio Astronomy
Bibliographic record
Abstract
This dissertation presents research on theory, design, EM modeling, fabrication, packaging and measurement of Monolithic Microwave Integrated Circuits (MMICs) and Radio Frequency Integrated Circuits (RFICs) for modern radio receivers. The purpose of the thesis is to demonstrate technology development for the future state of the art radio telescopes such as the Dish Verification Array (DVA-2), next generation Very Large Array (ngVLA) and Canadian Hydrogen Observatory and Radio-transient Detector (CHORD). The goal is to design integrated circuits that address the unique challenges of each radio telescope frontend in the microwave and millimeter wave regime ranging 1-120 GHz. Low noise figure, high gain and wide bandwidth cryogenic and room temperature Low Noise Amplifiers (LNA) and wideband high conversion gain mm-wave mixers are the critical components of a radio receiver. This work aims to research and develop integrated circuits based on four semiconductor technologies: GaAs pHEMT, GaAs mHEMT, InP HEMT and SiGe BiCMOS. Each technology has its unique advantages that make it the optimum choice for each specific block in the radio receiver chain. GaAs mHEMT and InP HEMT offer the ultimate low noise and high operational frequency that is suitable for cryogenic LNAs. GaAs pHEMT features low noise, excellent repeatability and medium power capacity that is advantageous in post amplifier (warm amplifier) and mixer design. SiGe BiCMOS with very high cut-off frequency HBTs and standard CMOS and multi-metal back end of line (BEOL) is the best option for millimeter-wave down-converter and post amplifier with high degree of integration. The fundamentals of each semiconductor technology are reviewed and the design methodology of four LNAs at, UHF (0.3-1.5 GHz), Ku (12-24 GHz), Ka (18-36 GHz) and Q (30-52 GHz) bands and three mm-wave mixers at Q (35-50 GHz and 33-55 GHz) and W (70-120 GHz) bands are presented with the focus on low noise, high gain, wide bandwidth and low input/output return loss. A co-design method is employed to account for packaging and wire bond effect. The designed MMICs and RFICs are validated by measurements of several prototypes, and compared to similar published works and commercially available chips that demonstrates their capability required by the next generation of radio telescopes.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.023 | 0.011 |
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".