A digital predistortion system based on a generalized memory polynomial for GaN power amplifiers

Modern power amplifiers based on GaN transistors face a number of problems related to their physical properties and operating conditions. The high output power of such power amplifiers is accompanied by significant nonlinear distortions, especially when operating in saturation mode. Amplifiers based on GaN transistors have pronounced «short» memory effects, which leads to the dependence of current distortions on previous signal states. At the same time, support for broadband signals requires high processing speeds and large computing resources. Classical digital pre-distortion methods do not always cope with the task of effectively compensating for real-time distortion for power amplifiers based on GaN transistors. These problems complicate the process of linearization of power amplifiers based on GaN transistors and require the development of new methods that can effectively compensate for non-linearities and memory effects without significantly increasing the cost and complexity of the system. The purpose of the work is to create and analyze the effectiveness of a digital pre-imaging system based on a generalized polynomial model with memory to improve the linearity and efficiency of power amplifiers based on GaN transistors in wireless communication systems. The paper presents the architecture of the digital preimage input system based on a generalized polynomial model with memory. The use of this model makes it possible to improve the efficiency of suppressing nonlinear distortions at the output of a power amplifier based on GaN transistors. Practical significance – the proposed architecture can be implemented on FPGAs, VLSI or SOC with a minimum amount of computing resources.