In this paper, we propose an efficient open-loop digital predistorter (DPD) derived from the dynamic deviation reduction-based Volterra series that allows compensation for both nonlinear distortion and memory effects induced by RF power amplifiers in wireless transmitters. In this approach, the parameters of the predistorter can be directly extracted from an offline system identification process. This eliminates the usual requirement for a closed-loop real-time parameter adaptation, which dramatically reduces the implementation complexity of the system. It is shown that a further reduction in system complexity can be achieved by applying under-sampling theory in the model extraction and utilizing parameter interpolation in the DPD implementation. Experimental results show that by utilizing this technique with only a small number of parameters, nonlinear distortion induced by the PA can be significantly reduced, as evaluated by both adjacent channel power ratio reduction and normalized root mean square error improvement. A comparison with a memoryless polynomial function based predistorter and an analysis of the impact of decresting are also presented.

Open-Loop Digital Predistorter for RF Power Amplifiers Using Dynamic Deviation Reduction-Based Volterra Series

https://www.dtc.umn.edu/s/resources/gg-se.pdf

A bibliography on nonlinear system identification

Some interesting properties of output frequencies of Volterra-type nonlinear systems are particularly investigated. These results provide a very novel and useful insight into the super-harmonic and inter-modulation phenomena in output frequency response of nonlinear systems, with consideration of the effects incurred by different nonlinear components in the system. The new properties theoretically demonstrate several fundamental output frequency characteristics and unveil clearly the mechanism of the interaction (or coupling effects) between different harmonic behaviors in system output frequency response incurred by different nonlinear components. These results have significance in the analysis and design of nonlinear systems and nonlinear filters in order to achieve a specific output spectrum in a desired frequency band by taking advantage of nonlinearities. They can provide an important guidance to modeling, identification, control and signal processing by using the Volterra series theory in practice.

Output Frequency Characteristics of Nonlinear Systems

Digital predistortion (DPD) is a popular approach for linearizing power amplifiers (PAs) in wireless base stations and improving system efficiency. The feedback path in a DPD system typically requires 5x signal bandwidth to accommodate the bandwidth expansion caused by the DPD and nonlinear PA. In this paper, we propose a new approach for adapting DPD parameters using direct learning and reduced bandwidth feedback. The new approach is capable of achieving near full-rate DPD performance and linearization bandwidth with significantly reduced feedback bandwidth. Measurement results on a Doherty PA achieved more than 20 dB corrections over 200 MHz bandwidth for a 2-carrier WCDMA signal spanning 40 MHz with only 81.92 MHz feedback bandwidth.

Digital predistortion using direct learning with reduced bandwidth feedback

Most conventional wideband digital predistortion (DPD) techniques require the use of a very high-speed analog-to- digital converter (ADC) in the feedback path. This paper proposes a novel technique, termed under-sampling restoration digital predistortion (USR-DPD), to linearize wideband power amplifiers (PAs) with ADCs that operate at sampling rates much lower than required by Nyquist limits for the predistorted band (under-sampling ADCs). The USR processing is implemented in an iterative way to restore full-band PA output information from the under-sampled output signal, allowing memory DPD models to be successfully extracted. The USR-DPD can operate in two modes: without and with a band-limiting filter in the feedback path. In comparison with conventional DPD techniques, the requirement for ADC sampling frequency can be significantly reduced using the USR-DPD approach. Experimental tests were realized for two PAs with numerous signals (10-, 20-, 40-, and 60-MHz long-term evolution signals) using different ADC sampling frequencies. The DPD with the under-sampling ADC could achieve comparable performances to its counterpart with a full-rate ADC, while using 3-5 times lower sampling frequency, and around -50-dBc adjacent channel power ratios were achieved.

Novel Technique for Wideband Digital Predistortion of Power Amplifiers With an Under-Sampling ADC

Volterra systems generally produce-due to nonlinearity-an output signal with a higher frequency range when compared with the input signal. Hence, it seems necessary to sample the input and output signals at twice the maximum frequency of the output signal. The article shows that it is sufficient to sample at twice the maximum frequency of the input signal. A discrete-time Volterra system also produces the additional frequency components that appear-due to aliasing-at the sampled output of a continuous-time Volterra system with an equivalent transfer function.

W.A. Frank

Papers

Sampling requirements for Volterra system identification