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  5. Energy Efficiency Optimization for Dense Networks
 
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Energy Efficiency Optimization for Dense Networks

Author(s)
Vu, Quang-Doanh  
Juntti, Markku  
Hong, Een-Kee  
Tran, Le-Nam  
Uri
http://hdl.handle.net/10197/11905
Date Issued
2019-02-01
Date Available
2021-02-01T17:22:12Z
Abstract
Dense networks open opportunities to optimize the network performance particularly from an energy efficiency perspective, since the total power consumption is a great concern as the number of devices is very large. The goal of this chapter is to provide a set of optimization tools applied in designing energy efficiency transmission for dense networks. Specifically, this chapter includes two parts. The first part introduces optimization techniques that are useful for energy efficiency optimization including concave-convex fractional programming, nontractable fractional programming, the alternating direction method of multipliers for distributed implementation. The second part is to demonstrate how these methods can be applied to dense networks with shared spectrum and small-cell dense networks being the case studies.
Sponsorship
Science Foundation Ireland
Type of Material
Book Chapter
Publisher
Wiley
Copyright (Published Version)
2019 Wiley
Subjects

ADMM

Dense networks

Dinkelbach's methods

Energy efficiency opt...

Parameter-free equiva...

Radio access technolo...

Success convex approx...

DOI
10.1002/9781119473756.ch8
Language
English
Status of Item
Peer reviewed
Journal
Duong, T.Q., Chu, X., Suraweera, H.A. (eds.). Ultra-dense Networks for 5G and Beyond
ISBN
9781119473695
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
File(s)
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Name

EEforDense_v2.pdf

Size

348.31 KB

Format

Adobe PDF

Checksum (MD5)

f9e855bf3b7abb144738044be0967ee8

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/.
All other content is subject to copyright.

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