Work

A Scalable Bandwidth and Frequency-Dependent DPD Linearizer for User Equipment Power Amplifiers With Nonflat Frequency Response

Year: 2023

Type: article

Abstract: This article presents a scalable digital predistortion (DPD) linearizer for handset power amplifiers (PAs) with nonflat frequency response and assuming a 5G scenario with dynamic resource blocks (RBs) reallocation. The scalable DPD model is designed to be both bandwidth and frequency-dependent, including some design constraints targeting a resource-efficient hardware implementation. In order to extract the most relevant basis functions that better trade-off the linearization performance and the required resources of a hardware implementation of the DPD, a feature selection technique based on a constrained version of the doubly orthogonal matching pursuit (DOMP) is proposed. The linearization performance of the proposed DPD method is evaluated on a PA system-on-chip (SoC), considering 5G new radio (NR) signals at different frequency locations and with different bandwidths within a 100 MHz channel.

Source: IEEE Transactions on Microwave Theory and Techniques

DOI: 10.1109/tmtt.2023.3324445

Authors: Wantao Li, Yan Guo, Gabriel Montoro, Pere L. Gilabert

Institutions: Universitat Politècnica de Catalunya, Huawei Technologies (China)

Language: English

Topic: Advanced Power Amplifier Design

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: green

Funders: Generalitat de Catalunya, Ministerio de Ciencia e Innovación, Agencia Estatal de Investigación