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  5. Preparing Linearity and Efficiency for 5G: Digital Predistortion for Dual-Band Doherty Power Amplifiers with Mixed-Mode Carrier Aggregation
 
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Preparing Linearity and Efficiency for 5G: Digital Predistortion for Dual-Band Doherty Power Amplifiers with Mixed-Mode Carrier Aggregation

Alternative Title
Digital Predistortion for Dual-Band Doherty Power Amplifiers with Mixed-Mode Carrier Aggregation
Author(s)
Kelly, Noel  
Cao, Wenhui  
Zhu, Anding  
Uri
http://hdl.handle.net/10197/8383
Date Issued
2017-02
Date Available
2017-03-02T16:36:13Z
Abstract
As new wireless communication standards seek to meet the myriad demands of today's end users, the traditional RF transmitter chain is faced with an evolving set of challenges. To maximize information throughput, signal bandwidths are continuously growing. In fourth-generation longterm evolution-advanced (also called LTE-A), for example, to meet the stated goals of 1-Gb/s downlink and 500-Mb/s uplink speeds, the carrier aggregation (CA) technique was introduced, expanding the maximum transmit bandwidth up to 100 MHz [1]. With mobile traffic expected to increase by a factor of 1,000 over the next decade, future fifth-generation (5G) systems will continue to place new demands on the transmit chain.
Sponsorship
European Commission - European Regional Development Fund
Science Foundation Ireland
Type of Material
Journal Article
Publisher
IEEE
Journal
IEEE Microwave Magazine
Volume
18
Issue
1
Start Page
76
End Page
84
Copyright (Published Version)
2017 IEEE
Subjects

Dual band

OFDM

Predistortion

Wireless communicatio...

DOI
10.1109/MMM.2016.2616185
Language
English
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/
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Final_PrePub_version_Digital_Predistortion_for_Dual_band_Doherty_Power_Amplifiers_with_Mixed_mode_Carrier_Aggregation_Kelly_Cao.pdf

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4.35 MB

Format

Adobe PDF

Checksum (MD5)

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Owning collection
Electrical and Electronic Engineering Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
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