未来5G移动通信系统中，功率放大器的线性化是研究的难点。数字预失真技术是目前线性化的主要的解决方案之一。由于大规模MIMO和毫米波通信等新技术的采用，5G移动通信系统构架将更加复杂，并且信号带宽超大，因此功放的非线性特性和数字预失真处理也变得十分复杂。本项目重点研究面向5G的宽带功放的非线性特性、行为建模方法和数字预失真技术。研究5G系统的数字预失真的新构架，探索降低数字预失真反馈接收通道ADC采样率和数字信号处理速率的新方法，并且采用分段线性函数为基函数，研究适用于5G的带限条件下的功率放大器模型和相应的自适应算法。在模型研究的基础上，设计高效、低成本和低复杂度的宽带数字预失真方法。本项目的研究将扩充宽带功放数字预失真方法和促进5G线性化技术的发展。

In future 5G mobile communication systems, the linearization techniques of power amplifiers are the research difficulties. Digital predistortion (DPD) is one of the major solutions of the linearization at present. The structure will be more complicated and the signal bandwidth will be large in 5G mobile communication systems because of the new technologies, such as massive MIMO and millimeter-wave communications. Thus, both the nonlinear characteristics and DPD of power amplifiers will also be complicated. Our project will focus on the nonlinear characteristics, behavioral modeling and DPD of power amplifiers in 5G mobile communication systems. It will explore the new DPD structure of 5G systems, the new methods for reducing the digital processing rate, and the solutions for reducing the sampling rate of the ADC in the feedback channel. The piecewise linear function-based models of 5G power amplifiers and the adaptive algorithms will be studied under the band-limited signal conditions. Based on the behavioral models, the wideband DPD method with low complexity, low cost and high efficiency will be designed. Our work will extend the DPD methodologies for broadband power amplifiers and promote the development of 5G linearization techniques.