Neural Network based Nonlinear Forward Model Identification for Digital MIMO Arrays under Load Modulation

In multi-antenna transmitters, antenna coupling may lead to load modulation of the PAs, making their nonlinear responses beam-dependent and compromising traditional digital predistortion solutions. This paper presents a methodology for nonlinear PA array modeling using time-delay neural networks (TDNNs), with specific focus on digital MIMO systems. RF measurements on an emulated 4 X 1 array at 2.1 GHz demonstrate the effectiveness of the proposed approach in accurately modeling the PA array under load modulation, while showing clear gains over current polynomial-based and TDNN-based state-of-the-art models.