Improving energy efficiency of massive memo using small cell network / Alizawati Mat Zim

Nowadays, the compaction of the cellular network resulted in increased demand in wireless data services. However, the cellular energy efficiency (EE) can be improved by densification the network topology, without bothering quality-of-service (QoS) constraint at the users. In this paper, small cell n...

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Main Author: Mat Zim, Alizawati
Format: Thesis
Language:en
Published: 2016
Subjects:
Online Access:https://ir.uitm.edu.my/id/eprint/69042/1/69042.pdf
https://ir.uitm.edu.my/id/eprint/69042/
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author Mat Zim, Alizawati
author_facet Mat Zim, Alizawati
author_sort Mat Zim, Alizawati
building Tun Abdul Razak Library
collection Institutional Repository
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
continent Asia
country Malaysia
description Nowadays, the compaction of the cellular network resulted in increased demand in wireless data services. However, the cellular energy efficiency (EE) can be improved by densification the network topology, without bothering quality-of-service (QoS) constraint at the users. In this paper, small cell network (SCN) is applied in massive MIMO (MM) and analyze the power consumption of these two densification approaches for different QoS constraints. For this paper, three beamforming (BF) algorithms are compared which are optimal BF is using only the base station (BS), multiflow regularized zero forcing (RZF) BF and optimal spatial soft-cell coordination BF. Numerical result compared with BF algorithm proposed in different simulation parameters and show that by increasing the number of small-cell access points (SCAs), the antennas per SCAs could enhance the total system energy efficiency.
format Thesis
id my.uitm.ir-69042
institution Universiti Teknologi Mara
language en
publishDate 2016
record_format eprints
spelling my.uitm.ir-690422023-02-02T15:01:54Z https://ir.uitm.edu.my/id/eprint/69042/ Improving energy efficiency of massive memo using small cell network / Alizawati Mat Zim Mat Zim, Alizawati Neural networks (Computer science) Nowadays, the compaction of the cellular network resulted in increased demand in wireless data services. However, the cellular energy efficiency (EE) can be improved by densification the network topology, without bothering quality-of-service (QoS) constraint at the users. In this paper, small cell network (SCN) is applied in massive MIMO (MM) and analyze the power consumption of these two densification approaches for different QoS constraints. For this paper, three beamforming (BF) algorithms are compared which are optimal BF is using only the base station (BS), multiflow regularized zero forcing (RZF) BF and optimal spatial soft-cell coordination BF. Numerical result compared with BF algorithm proposed in different simulation parameters and show that by increasing the number of small-cell access points (SCAs), the antennas per SCAs could enhance the total system energy efficiency. 2016 Thesis NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/69042/1/69042.pdf Improving energy efficiency of massive memo using small cell network / Alizawati Mat Zim. (2016) Masters thesis, thesis, Universiti Teknologi MARA (UiTM).
spellingShingle Neural networks (Computer science)
Mat Zim, Alizawati
Improving energy efficiency of massive memo using small cell network / Alizawati Mat Zim
title Improving energy efficiency of massive memo using small cell network / Alizawati Mat Zim
title_full Improving energy efficiency of massive memo using small cell network / Alizawati Mat Zim
title_fullStr Improving energy efficiency of massive memo using small cell network / Alizawati Mat Zim
title_full_unstemmed Improving energy efficiency of massive memo using small cell network / Alizawati Mat Zim
title_short Improving energy efficiency of massive memo using small cell network / Alizawati Mat Zim
title_sort improving energy efficiency of massive memo using small cell network / alizawati mat zim
topic Neural networks (Computer science)
url https://ir.uitm.edu.my/id/eprint/69042/1/69042.pdf
https://ir.uitm.edu.my/id/eprint/69042/
url_provider http://ir.uitm.edu.my/