Proceedings of the 2015 5th International Conference on Computer Sciences and Automation Engineering

Energy Efficiency of Massive-MIMO Heterogeneous Network

Authors
Hui Bao, Pengbo Fang
Corresponding Author
Hui Bao
Available Online February 2016.
DOI
10.2991/iccsae-15.2016.105How to use a DOI?
Keywords
Massive MIMO; heterogeneous network; energy efficiency; Joint Spatial
Abstract

Massive massive multiple-input multiple-output(MIMO) and heterogeneous networks are two Potential technologies in the 5G. The application of Massive-MIMO to heterogeneous network can effectively eliminate the interference and improve energy efficiency.In this paper, the network is optimized by using Joint Spatial Division and Multiplexing(JSDM) and zero forcing algorithm,analyzing the spectrum efficiency and energy efficiency of the heterogeneous network.The relationship between the energy efficiency and the number of antennas and the transmission power of the base station are considered by simulation.

Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2015 5th International Conference on Computer Sciences and Automation Engineering
Series
Advances in Computer Science Research
Publication Date
February 2016
ISBN
978-94-6252-156-8
ISSN
2352-538X
DOI
10.2991/iccsae-15.2016.105How to use a DOI?
Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Hui Bao
AU  - Pengbo Fang
PY  - 2016/02
DA  - 2016/02
TI  - Energy Efficiency of Massive-MIMO Heterogeneous Network
BT  - Proceedings of the 2015 5th International Conference on Computer Sciences and Automation Engineering
PB  - Atlantis Press
SP  - 571
EP  - 574
SN  - 2352-538X
UR  - https://doi.org/10.2991/iccsae-15.2016.105
DO  - 10.2991/iccsae-15.2016.105
ID  - Bao2016/02
ER  -