Design of an efficiency enhanced wideband Doherty power amplifier based on synthesising of a modified harmonic‐control load modulation network
Bibliographic record
Abstract
Abstract A design of a broadband Doherty power amplifier (DPA) using a novel harmonic control network (HCN) is presented. The DPA structure focused on manipulating harmonic components using this new HCN to enhance the bandwidth of operation and power efficiency. The proposed HCN combines a third harmonic suppression network (THSN) with the second harmonic impedance inverter circuit (SHIIC). In the design, the second harmonic component of the main transistor and the peaking transistor are short‐circuited by their associated SHIIC. Additionally, the carefully designed SHIIC and THSN circuit placed between the main and peaking transistors realise open circuit conditions at the third harmonic for both transistors at the saturation state and back‐off regions. Side by side with the aid of the properly designed post‐matching tuned network (PMTN), these harmonic loading conditions make both amplifiers to operate in continuous Class‐F modes with enhanced‐added efficiencies over wideband conditions. As a result, a succession of highly efficient DPA modes can be formed over a continuous frequency range in the full Doherty region, resulting in a reduced‐size enhanced power efficiency wideband DPA. For verification, a wideband DPA operating from 1.1 to 1.8 GHz was designed and implemented using the proposed topology. The measured drain efficiency of the implemented DPA at 6‐dB back‐off is 52.5%–67.5%, while the saturated power across the specified bandwidth is 43–43.7 dBm. The fabricated DPA exhibits an average efficiency of 48.7%–59.4%, when supplied by a 40‐MHz long‐term evolution (LTE) signal with a 7.5‐dB peak‐to‐average power ratio (PAPR). Performing digital pre‐distortion (DPD) improves the adjacent channel power ratio (ACLR) from −25.8 dBc to −47.6 dBc.
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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 | 0.000 |
| 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".