Dynamic behavioral modeling of RF power amplifiers based on decomposed piecewise machine learning technique
Jialin Cai, Justin B. King, Chao Yu, Baicao Pan, Lingling Sun, Jun Liu
Multi-device radio frequency power amplifiers (PAs) often exhibit strongly non-linear behavior in combination with long-term memory effects, leading to an extremely challenging model development cycle. This paper presents a new, dynamic, behavioral modeling technique, based on a combination of the real-valued decomposed piecewise method and concepts from the field of machine learning. The underlyi