Research on linearisation of power amplifier based on digital pre-distortion

Abstract

The power amplifier is an important device in the communication system, and its non-linear characteristics will lead to serious distortion of the output signal, reducing the performance of the communication system. In order to solve the problem of non-linearity in a power amplifier, this study proposes an adaptive learning algorithm based on a digital pre-distortion structure, which combines direct learning and indirect learning structure. It improves the accuracy of pre-distorter parameter and has the faster convergence speed. The pre-distortion device parameters are constantly modified to achieve a good linear effect by using the recursive least square adaptive algorithm. The simulation results show that this structure effectively compensates the output signal distortion of the power amplifier, improves the linearisation degree of the power amplifier and reduces the in-band distortion and adjacent channel leakage ratio.

Keywords

• learning (artificial intelligence)
• distortion
• power amplifiers
• power amplifier
• communication system
• nonlinear characteristics
• serious distortion
• adaptive learning algorithm
• digital pre-distortion structure
• indirect learning structure
• pre-distorter parameter
• pre-distortion device parameters
• output signal distortion
• in-band distortion