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Efficient Sampling of Genetically Encoded Biosensor Design Space Enabled with a Design of Experiments and Automation Workflow
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Multi-Objective Optimization Design of Doherty Power Amplifier Circuits Based on Non-Dominated Sorting Genetic

Hanbin Qu1,2, Xiaopeng Zhang1,2, Sixin Gao1,2

  • 1Hebei Xinhuabei Integrated Circuit Co., Ltd., Shijiazhuang 050200, China.

Micromachines
|May 27, 2026
PubMed
Summary
This summary is machine-generated.

A new Non-dominated Sorting Genetic Algorithm-II (NSGA-II) method optimizes Doherty power amplifier circuits, improving efficiency and output power. This advanced technique enhances performance for complex power amplifier designs.

Keywords:
Doherty power amplifier (DPA)Non-dominated Sorting Genetic Algorithm-II (NSGA-II)efficiencylinearity

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Area of Science:

  • Electrical Engineering
  • Computer Science

Background:

  • Conventional optimization algorithms struggle with multi-objective problems, leading to long computation times and local optima.
  • Power amplifier (PA) circuit design requires efficient optimization for improved performance.

Purpose of the Study:

  • To propose and evaluate a multi-objective optimization method using Non-dominated Sorting Genetic Algorithm-II (NSGA-II) for Doherty power amplifier circuits.
  • To enhance the efficiency and output power of PA circuits.

Main Methods:

  • Implemented a multi-objective optimization strategy based on the Non-dominated Sorting Genetic Algorithm-II (NSGA-II).
  • Applied the NSGA-II method to optimize Doherty power amplifier circuit designs.

Main Results:

  • Achieved a 6.4% increase in saturation efficiency.
  • Demonstrated a 3.3% increase in 6 dB roll-off efficiency.
  • Obtained a 1 dB increase in saturation output power at 2.63 GHz compared to traditional methods.

Conclusions:

  • The NSGA-II based method effectively optimizes Doherty power amplifier circuits.
  • This approach enhances overall circuit performance and enables multi-objective design for complex PA circuits.