A FLEXIBLE DUAL-INFLECTION POINT RF PREDISTORTION LINEARIZER FOR MICROWAVE POWER AMPLIFIERS
Bibliographic record
Abstract
Abstract—This paper presents a very flexible and generic design of a diode-based RF predistortion linearizer that can correct for the dual-inflection point type compression characteristics found in the gain profile of metal semiconductor field effect transistor (MESFET) based and Doherty power amplifiers. It consists of a circuit configuration that has the head-tail configuration of Schottky diodes, complemented with a p-intrinsic-n (PIN) diode in parallel, at two ports of a 90◦ hybrid coupler for improving the performance of the linearizer. The use of a PIN diode in the linearizer provides it with an extra level of freedom in achieving the desired characteristic. Overall, the linearizer is equipped with three degrees of freedom and hence possesses the capability to achieve output characteristics that can be employed in linearizing various types of power amplifiers. The proposed linearizer has been shown to simultaneously improve the third- and fifth-order intermodulation distortions of a commercial ZHL-4240 gallium arsenide field effect transistor (GaAs FET) based power amplifier over a 10 dB power range. 1.
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 | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".