Modified Doherty Amplifier With Extended Bandwidth and Back-Off Power Range Using Optimized Peak Combining Current Ratio
Bibliographic record
Abstract
In this paper, a novel modified Doherty power amplifier (DPA) that allows for extended output back-off (OBO) range, improved power utilization factor (PUF), and increased peak power over a broad bandwidth is proposed. It starts with an in-depth analysis of the modified DPA circuitry that first revealed the ability to control the impedances seen by the main transistor versus frequency by properly setting the magnitude and phase of the ratio between the peaks of the combining currents. This is then exploited to maximize the peak power and enhance the achievable bandwidth. Furthermore, a complex-to-real output matching network is incorporated in the auxiliary path and its parameters are carefully chosen to produce proper load modulation while satisfying the required peak combining current ratio. For validation purpose, a DPA prototype is designed to operate over the frequency range of 1.35-2.05 GHz with an OBO of 9 dB. Under the continuous-wave excitation, the DPA prototype maintained the drain efficiency (DE) of 52%-55% and 65%-75% at 9-dB OBO and peak power, respectively, over the entire targeted band. In addition, the measured peak power and PUF were about 42 dBm and higher than 0.9, respectively. The linearizability of the DPA prototype using digital predistortion (DPD) with memory was assessed while being driven with a 40-MHz carrier-aggregated signal with a peak-to-average power ratio of 8.9 dB and at an average output power of 33 dBm. When the carrier frequency is swept over the entire band, the measurement revealed an adjacent channel leakage ratio of better than -46.5 dBc after DPD with an average DE of 49.3%-53%.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".