Millimeter Wave SOI-CMOS Power Amplifier With Enhanced AM-PM Characteristic
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Bibliographic record
Abstract
This paper proposes a novel inter-stage load-pull characterization method to enhance the linearity of millimeter wave integrated power amplifiers (PAs) by minimizing their amplitude-to-phase (AM-PM) distortion without worsening their AM-AM or efficiency performances. The proposed method identifies the optimal solution for the inter-stage matching network which enables the synthesis of a driver stage AM-PM characteristic that is complementary to that of the power stage; consequently, reducing the overall AM-PM distortion of the PA. The proposed technique is applied to design a proof-of-concept 28-31 GHz PA demonstrator using 45 nm silicon-on-insulator CMOS technology. The measurement results obtained under continuous wave excitation at 29 GHz demonstrate an excellent AM-PM characteristic, with phase distortions as low as 0.2° at the 1-dB compression power level of 13.9 dBm and less than 1° at an output power level of up to 16 dBm (very close to the saturation power of 16.6 dBm). This enhanced AM-PM linearity improves the linearizability of the PA. This was confirmed by testing the PA with a 64 quadrature amplitude modulated test signal with an instantaneous bandwidth of 800 MHz. Without applying any digital pre-distortion (DPD) technique, the PA delivers a power added efficiency (PAE) of 8.7% at an average output power (Pavg) of 9.4 dBm while maintaining an error vector magnitude (EVM) of -25 dB. However, after applying a very simple memoryless DPD function with only four coefficients, the PA can operate at a higher Pavg of 11.1 dBm with a much better PAE of 12.2% while still maintaining an acceptable EVM of -25.2 dB. Thanks to the proposed technique, the PAE of the proposed PA can be improved by 40% with a very simple application of a low cost and low complexity DPD technique.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 it