Heuristic algorithms for power amplifier behavioral modeling
This letter presents the use of two heuristic search algorithms, named simulated annealing and genetic algorithms, for the extraction of power amplifier (PA) behavioral model parameters. Their application in this letter consists in determining the memory length and the most significant delays of the...
| Autores: | , , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2007 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/2026 |
| Acceso en línea: | https://hdl.handle.net/2117/2026 |
| Access Level: | acceso abierto |
| Palabra clave: | Power amplifiers Heuristic programming Heuristic algorithms Behavioral modeling Heurística Amplificadors Àrees temàtiques de la UPC::Enginyeria electrònica::Electrònica de potència |
| Sumario: | This letter presents the use of two heuristic search algorithms, named simulated annealing and genetic algorithms, for the extraction of power amplifier (PA) behavioral model parameters. Their application in this letter consists in determining the memory length and the most significant delays of the considered model structure. Two PA behavioral models have been considered: an augmented nonlinear moving average model and a nonlinear auto-regressive moving average model. By using WCDMA signals measured from a three-stage LDMOS class AB PA, both PA models were extracted. Finally, results presenting the advantages of using these heuristic search algorithms are provided. |
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