2001Electronics LettersRequires access

Digital predistortion of wideband signals basedon power amplifier model with memory

Je Duk Kim, K. Konstantinou

Open publisher page 927 citations

Abstract

Memory effects in the power amplifier limit the performance of digital predistortion for wideband signals. Novel algorithms that take into account such effects are proposed. Measured results are presented for single and multicarrier UMTS signals to demonstrate the effectiveness of the new approach.

About this research paper

What this paper is about

Memory effects in the power amplifier limit the performance of digital predistortion for wideband signals. Novel algorithms that take into account such effects are proposed. Measured results are presented for single and multicarrier UMTS signals to demonstrate the effectiveness of the new approach.

Why it matters

OpenAlex reports 927 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

Memory effects in the power amplifier limit the performance of digital predistortion for wideband signals. Novel algorithms that take into account such effects are proposed. Measured results are presented for single and multicarrier UMTS signals to demonstrate the effectiveness of the new approach.

Key concepts: Predistortion, Wideband, Amplifier, Electronic engineering, Computer science, Power (physics), UMTS frequency bands, Limit (mathematics)

Related papers

Back to paper searchBrowse research topicsOriginal source
Digital predistortion of wideband signals basedon power amplifier model with memory — Research Paper | ScholarLens