Please use this identifier to cite or link to this item:
Title: A Novel Design Approach for 5G Massive MIMO and NB-IoT Green Networks Using a Hybrid Jaya-Differential Evolution Algorithm
Authors: Goudos, Sotirios K.
Deruyck, Margot
Plets, David
Martens, Luc
Psannis, Kostas E.
Sarigiannidis, Panagiotis
Joseph, Wout
Type: Article
Subjects: FRASCATI::Engineering and technology
Keywords: Massive MIMO
green networks
evolutionary algorithms
network design
hybrid networks
network planning
power consumption
Issue Date: 30-Jul-2019
Publisher: IEEE
Source: IEEE Access
Volume: 7
First Page: 105687
Last Page: 105700
Abstract: Our main objective is to reduce power consumption by responding to the instantaneous bit rate demand by the user for 4th Generation (4G) and 5th Generation (5G) Massive MIMO network configurations. Moreover, we present and address the problem of designing green LTE networks with the Internet of Things (IoT) nodes. We consider the new NarrowBand-IoT (NB-IoT) wireless technology that will emerge in current and future access networks. In this context, we apply emerging evolutionary algorithms in the context of green network design. We investigate three different cases to show the performance of the new proposed algorithm, namely the 4G, 5G Massive MIMO, and the NB-IoT technologies. More specifically, we investigate the Teaching-Learning-Optimization (TLBO), the Jaya algorithm, the self-adaptive differential evolution jDE algorithm, and other hybrid algorithms. We introduce a new hybrid algorithm named Jaya-jDE that uses concepts from both Jaya and jDE algorithms in an effective way. The results show that 5G Massive MIMO networks require about 50% less power consumption than the 4G ones, and the NB-IoT in-band deployment requires about 10% less power than guard-band deployment. Moreover, Jaya-jDE emerges as the best algorithm based on the results.
ISSN: 2169-3536
Electronic ISSN: 2169-3536
Other Identifiers: 10.1109/ACCESS.2019.2932042
Appears in Collections:Department of Applied Informatics

Files in This Item:
File Description SizeFormat 
Psannis open Access 2019.pdfPsannis open Access 2019.pdf9,74 MBAdobe PDFView/Open

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.