A Complexity-Reduced 2D Behavioral Modeling Configuration for the Linearization of Concurrent Dual-Band Transmitters

This paper proposes a complexity-reduced 2D memory polynomial model (MPM) for the linearization of concurrent dual-band radio transmitters. The proposed model presents a new configuration of a 2D MPM to be used for the modeling and digital predistortion (DPD) of power amplifiers (PAs). The presented technique alleviates the oversizing issue faced in the conventional 2D model by separating the highly nonlinear memoryless and mildly nonlinear dynamic behaviors, which results in a smaller number of coefficients, and therefore, reduced computational complexity is achieved. With the measurement setup, the proposed model achieved relatively the same performance as the conventional formulation while significantly reducing the model dimension by about 50%. The experiments were carried out using two 5G new radio (NR) signals with a bandwidth of 20 MHz and a PAPR of 8 dB each.