Work

Minimizing Training Signal Length for Power Amplifier Characterization and Linearization

Year: 2023

Type: article

Abstract: Wireless communication faces a significant challenge in meeting latency and power consumption requirements due, in large part, to the nonlinear behavior of power amplifiers (PAs) requiring digital predistortion (DPD). Calculating the parameters for DPD can be computationally demanding, especially with multiple transmitter paths in multiple-input–multiple-output (MIMO) systems. This research formulates a novel optimized training signal for DPD (OTS-DPD) that minimizes the number of samples needed to implement DPD while maintaining optimum PA linearization performance. Experimental validation of the DPD performance for the novel OTS-DPD signal demonstrates it outperforms a standard 5G orthogonal frequency division multiplexing (OFDM) signal and uses significantly fewer samples.

Source: IEEE Microwave and Wireless Technology Letters

DOI: 10.1109/lmwt.2023.3317509

Authors: Rahul Mushini, Yiyue Jiang, Miriam Leeser, John Dooley

Institutions: National University of Ireland, Maynooth, Northeastern University

Language: English

Topic: Advanced Power Amplifier Design

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $2,345

Funder: European Regional Development Fund