Mitigation of Bandwidth Limitation in Wireless Doherty Amplifiers With Substantial Bandwidth Enhancement Using Digital Techniques
Bibliographic record
Abstract
This paper proposes a new method for extending the bandwidth of Doherty power amplifiers (PAs) in the digital domain. The bandwidth enhancement is achieved through a frequency-selective pre-compensation mechanism that is derived to prevent the efficiency degradation that naturally occurs as the frequency of operation deviates from the center frequency. A methodical analysis of the frequency response of the conventional Doherty PA and that of the proposed Doherty PA is carried out to point out the limitations of the former and demonstrate the capability of the latter in recovering the bandwidth. Over the frequency range spanning from 1.96 to 2.46 GHz, the measured drain efficiency at 6-7-dB output power back-off is higher than 40% for the proposed Doherty PA. Such efficiency performance is achievable only from 2.04 to 2.22 GHz using the conventional Doherty PA. Hence, the bandwidth is enhanced from 180 to 500 MHz, which corresponds to an increase by a factor of 2.8 (i.e., almost triple). By applying the proposed methodology, a Doherty PA that is originally designed at the center frequency of 2.14 GHz for downlink wideband code division multiple access became operative at 1.98-GHz uplink wideband code division multiple access (UL-WCDMA), 2.22-GHz long-term evolution (LTE), and 2.34-GHz worldwide interoperability for microwave access (WiMAX) bands. The average drain efficiencies for UL-WCDMA, LTE, and WiMAX applications, were 40.1%, 44.2%, and 41.4%, respectively, using the proposed Doherty PA, and 37%, 37.3%, and 35.2%, respectively, using the conventional Doherty PA.
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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 | 0.001 |
| 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 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".