volume | PIER Journals

Abstract

A modified generalized memory polynomial model (MGMP) is proposed for RF power amplifiers (PAs). The MGMP model is derived by applying complexity-reduced technique to the generalized memory polynomial model (GMP)， and the least square (LS) algorithm is used for coefficient extraction. The proposed MGMP model is assessed using a GaN Class-F PA driven by two modulated signals (a WCDMA 1001 signal and a single carrier 16 QAM signal with 20 MHz bandwidth). The experimental results demonstrate that the MGMP model outperforms the memory polynomial (MP) model and the generalized memory polynomial (GMP) model. Compared with MP model, the MGMP model shows a normalized mean square error (NMSE) improvement of 2.13 dB in forward modeling, average adjacent channel power ratio (ACPR) improvement of 2.62/2.11 dB in the DPD application with almost identical number of model coefficients. In contrast with the GMP model, the MGMP model can achieve comparable forward modeling and linearization performance results, but reduces approximately 40% of coefficients.

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Dr. Gang Sun

Dr. Cuiping Yu

Dr. Yuan'an Liu

Dr. Shulan Li

Dr. Jiuchao Li