Comparison of a genetic programming approach with ANFIS for power amplifier behavioral modeling and FPGA implementation

Created by W.Langdon from gp-bibliography.bib Revision:1.8010

@Article{Galaviz-Aguilar:2019:SC,

• author = "Jose Alejandro Galaviz-Aguilar and Patrick Roblin and Jose Ricardo Cardenas-Valdez and Emigdio Z.-Flores and Leonardo Trujillo and Jose-Cruz Nunez Perez and Oliver Schuetze",
• title = "Comparison of a genetic programming approach with {ANFIS} for power amplifier behavioral modeling and {FPGA} implementation",
• journal = "Soft Computing",
• year = "2019",
• volume = "23",
• number = "7",
• pages = "2463--2481",
• keywords = "genetic algorithms, genetic programming, anfis digital predistortion linearisation power amplifier modelling radio frequency",
• ISSN = "1432-7643",
• bibsource = "DBLP, http://dblp.uni-trier.de/db/journals/soco/soco23.html#Galaviz-Aguilar19",
• DOI = "doi:10.1007/s00500-017-2941-8",
• abstract = "Accurate modelling of power amplifiers (PA) is of up most importance in the design process of wireless communication systems where a high linearity and efficiency is required. To deal with the nonlinear behaviour of PAs effectively a linearisation stage is applied to minimise the distortions of in-band and adjacent transmission channels, which translate to an improvement of the signal integrity and the operation cost of the transmitter system. This paper presents a method based on genetic programming with a local search heuristic (GP-LS) to emulate the electrical memory effects by using the characteristic conversion curves of the radio frequency (RF) PA NXP Semiconductor of 10 W GaN HEMT working at 2.34 GHz. This method is compared with an Adaptive Neuro-Fuzzy Inference Systems (ANFIS) through several performance metrics (NMSE, MAE and correlation coefficient), with GP-LS achieving a better modelling accuracy. Moreover, the models produced by GP-LS permit a reduction in the required hardware resources, when it is implemented on a Field-Programmable Gate Array through the DSP Builder tool. The models are derived using a data-driven approach, posed in two different ways. Firstly, experiments are performed using a testbed Arria V GX for a flexible vector signal generation that provides the raw data of the PA characterisation using an LTE-Advanced signal with 10-MHz bandwidth. Secondly, the modelling is derived from a filtered version of the data and then adding a high-frequency signal as a post processing step to approximate the true behaviour of the system. In both cases, the models are generated with ANFIS and GP-LS, performing extensive logic-based simulations and implementing the models on a Cyclone III development board. Both approaches are compared based on accuracy and required hardware resources, with GP-LS substantially outperforming ANFIS. These results suggest that the GP-LS models can be implemented in a digital pre-distortion chain and used in the linearization stage for a RF-PA.",
• notes = "journals/soco/Galaviz-Aguilar19",

}

Genetic Programming entries for Jose Alejandro Galaviz-Aguilar Patrick Roblin Jose Ricardo Cardenas Valdez Emigdio Z-Flores Leonardo Trujillo Jose Cruz Nunez Perez Oliver Schuetze

Citations