A Modified Decomposed Vector Rotation-Based Behavioral Model With Efficient Hardware Implementation for Digital Predistortion of RF Power Amplifiers

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Title: A Modified Decomposed Vector Rotation-Based Behavioral Model With Efficient Hardware Implementation for Digital Predistortion of RF Power Amplifiers
Authors: Cao, WenhuiZhu, Anding
Permanent link: http://hdl.handle.net/10197/8380
Date: 23-Jan-2017
Online since: 2017-02-28T13:35:58Z
Abstract: This paper proposes a novel hardware implementation strategy to achieve low-cost design for digital predistortion (DPD) of radio frequency (RF) power amplifiers (PAs) using a modified decomposed vector rotation (DVR)-based behavioral model. To make the model hardware friendly, we first modify the model into a sub-decomposed format which significantly reduces the computational complexity in model extraction. We then reassemble the coefficients and propose a simple digital implementation structure for real-time signal processing in the transmit path. A new Dual-Direction COordinate Rotation DIgital Computer (DD-CORDIC) design is also proposed to simultaneously calculate both magnitude and ejθn values to facilitate the model implementation. To validate hardware implementation, a wide-band signal is employed to evaluate the performance with a Doherty power amplifier. Experimental results show that the proposed approach can achieve comparable performance with much lower system complexity compared to that using the conventional approaches.
Type of material: Journal Article
Publisher: IEEE
Journal: IEEE Transactions on Microwave Theory and Techniques
Volume: PP
Issue: 99
Start page: 1
End page: 10
Copyright (published version): 2017 IEEE
Keywords: Behavioral modelCORDICDigital predistortionModel extractionPower amplifierRadio frequency
DOI: 10.1109/TMTT.2016.2640318
Language: en
Status of Item: Peer reviewed
This item is made available under a Creative Commons License: https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
Appears in Collections:Electrical and Electronic Engineering Research Collection

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