A Compact Ka/Q Dual-Band GaAs MMIC Doherty Power Amplifier With Simplified Offset Lines for 5G Applications
Bibliographic record
Abstract
In this paper, a Ka/Q dual-band Doherty power amplifier (DPA) with simplified offset lines is implemented in a 0.1-μm gallium arsenide (GaAs) process. It is found that the dual-band transmission lines (TLs) employed in the sub-6-GHz dual-band DPA are not suitable to be used as the offset lines in millimeter-wave (mm-wave) dual-band DPAs due to their large sizes and insert losses. An in-depth analysis reveals that the phase requirement of the offset lines can be relaxed, and the DPA exhibits a reasonable performance in a certain phase-shift range. A novel design method is proposed to realize offset lines using simple TLs, which can satisfy the phase-shift ranges in dual bands by choosing a proper electrical length. To enhance the gain of the DPA, a reversed uneven power splitter is adopted to deliver more power to the main power amplifier (PA). The fabricated DPA achieves an output power of 25.4/25.2 dBm, a peak power-added efficiency (PAE) of 33%/25%, and a 6-dB back-off PAE of 22%/17% at 29/46 GHz, respectively, with a compact size of 2.2 1.4 mm2. Applying a 20-MHZ 64-quadraticamplitude modulation (QAM) signal with a 7.7-dB peak-toaverage power ratio (PAPR), the measured average output power, PAE, and error vector magnitude (EVM) at 29/46 GHz are 18.4/19 dBm, 17%/15%, and 1.5%/1.1% after linearization, respectively. To the best of our knowledge, the proposed DPA is the first demonstration of mm-wave dual-band DPAs that do not require any additional switching or reconfiguration.
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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 | 0.000 | 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 | 0.000 |
| 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".