predistortion device

Abstract

The present disclosure relates to a predistortion device (100) for a non-linear PA device (101), comprising: an input terminal (102) for receiving an input signal (106); a predistortion filter (103), which connected between the input terminal (102) and the non-linear PA device (101); a first delay element (105), coupled to the input terminal (102) and configured to delay the input signal (106) by a time delay D to provide a delayed input signal (104); and an adaptive filter unit (120), which includes an adjustment unit (109) and has adjustable filter weights and is configured to perform the delayed input signal (104) A filtered adaptive filter (107), wherein the adjustment unit is configured to process the adaptive algorithm based on the delayed input signal (104) to adjust the filter weights of the adaptive filter (107) and to the adaptive filter Both the adaptive filter (107) and the adjustment unit (109) are coupled to the first delay element (105) to provide the same adjusted filter weights ) to receive the same delayed input signal (104).

Description

technical field [0001] The present disclosure relates to a predistortion device for a nonlinear power amplifier (PA) device. The invention also relates to a digital predistortion arrangement for a nonlinear PA used in a radio transmitter of a communication system. Background technique [0002] PA linearization problems arise in devices of communication systems where the transmitter's PA operates in the saturation region, which provides high efficiency but suffers from non-linear distortion. [0003] The problem of PA linearization is usually solved by applying predistortion to the PA input signal so that the output signal of the cascade of predistorter and PA is undistorted or almost undistorted. Since predistortion is usually implemented in the digital domain, ie based on the use of digital signal processing principles, this technique is called digital predistortion and the predistortion device is called a digital predistorter (Digital Predistorter, DPD). The DPD produces...

AI Technical Summary

Problems solved by technology

[0011] There are two main problems as indicated below which limit what is hereinafter referred to as traditional DPD cf. Figure 7 The efficiency of the DPD 700

[0012] First problem: compared to the case when both the adaptive filter 701 and the adaptive algorithm 713 will use the same input signal x(k) 702 see equation (5) below, the conventional direct learning DPD 700 The step size μ in the gradient search based adaptive algorithm used in max must have a small value, see equation (3) below

Smaller step size values ​​increase the duration of the transient response of the gradient search based adaptive algorithm, since the response increases if the step size decreases

[0013] Second question: Traditional direct learning DPD 700, see Figure 7 , the Recursive Least Square (RLS) adaptive algorithm, which is a more efficient algorithm compared with the gradient search-based adaptive algorithm, cannot be used because the RLS algorithm does not have parameters (such as step size), so the RLS algorithm becomes unstable in this architecture

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