SINR loss and user selection in massive MU‐MISO systems with ZFBF
Separating highly correlated users can reduce the loss caused by spatial correlation (SC) in multiuser multiple‐input multiple‐output (MU‐MIMO) systems. However, few accurate analyses of the loss caused by SC have been conducted. In this study, we define signal‐to‐interference‐plus‐noise ratio (SINR...
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Online Access: | https://doi.org/10.4218/etrij.2018-0376 |
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doaj-af51a9af88b7406890b134660af5b26f2020-11-25T02:51:19ZengElectronics and Telecommunications Research Institute (ETRI)ETRI Journal1225-64632019-04-0141563764710.4218/etrij.2018-037610.4218/etrij.2018-0376SINR loss and user selection in massive MU‐MISO systems with ZFBFMengshi HuYongyu ChangTianyi ZengBin WangSeparating highly correlated users can reduce the loss caused by spatial correlation (SC) in multiuser multiple‐input multiple‐output (MU‐MIMO) systems. However, few accurate analyses of the loss caused by SC have been conducted. In this study, we define signal‐to‐interference‐plus‐noise ratio (SINR) loss to characterize it in multiuser multiple‐input single‐output (MU‐MISO) systems, and use coefficient of correlation (CoC) to describe the SC between users. A formula is deduced to show the accurate relation between SINR loss and CoC. Based on this relation, we propose a user selection method that utilizes CoC to minimize the average SINR loss of users in massive MU‐MISO systems. Simulation results verify the correctness of the relation and show that the proposed user selection method is very effective at reducing the loss caused by SC in massive MU‐MISO systems.https://doi.org/10.4218/etrij.2018-0376coefficient of correlationmultiuser multiple‐input single‐outputsignal‐to‐interference‐plus‐noise ratio lossspatial correlationuser selection |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Mengshi Hu Yongyu Chang Tianyi Zeng Bin Wang |
spellingShingle |
Mengshi Hu Yongyu Chang Tianyi Zeng Bin Wang SINR loss and user selection in massive MU‐MISO systems with ZFBF ETRI Journal coefficient of correlation multiuser multiple‐input single‐output signal‐to‐interference‐plus‐noise ratio loss spatial correlation user selection |
author_facet |
Mengshi Hu Yongyu Chang Tianyi Zeng Bin Wang |
author_sort |
Mengshi Hu |
title |
SINR loss and user selection in massive MU‐MISO systems with ZFBF |
title_short |
SINR loss and user selection in massive MU‐MISO systems with ZFBF |
title_full |
SINR loss and user selection in massive MU‐MISO systems with ZFBF |
title_fullStr |
SINR loss and user selection in massive MU‐MISO systems with ZFBF |
title_full_unstemmed |
SINR loss and user selection in massive MU‐MISO systems with ZFBF |
title_sort |
sinr loss and user selection in massive mu‐miso systems with zfbf |
publisher |
Electronics and Telecommunications Research Institute (ETRI) |
series |
ETRI Journal |
issn |
1225-6463 |
publishDate |
2019-04-01 |
description |
Separating highly correlated users can reduce the loss caused by spatial correlation (SC) in multiuser multiple‐input multiple‐output (MU‐MIMO) systems. However, few accurate analyses of the loss caused by SC have been conducted. In this study, we define signal‐to‐interference‐plus‐noise ratio (SINR) loss to characterize it in multiuser multiple‐input single‐output (MU‐MISO) systems, and use coefficient of correlation (CoC) to describe the SC between users. A formula is deduced to show the accurate relation between SINR loss and CoC. Based on this relation, we propose a user selection method that utilizes CoC to minimize the average SINR loss of users in massive MU‐MISO systems. Simulation results verify the correctness of the relation and show that the proposed user selection method is very effective at reducing the loss caused by SC in massive MU‐MISO systems. |
topic |
coefficient of correlation multiuser multiple‐input single‐output signal‐to‐interference‐plus‐noise ratio loss spatial correlation user selection |
url |
https://doi.org/10.4218/etrij.2018-0376 |
work_keys_str_mv |
AT mengshihu sinrlossanduserselectioninmassivemumisosystemswithzfbf AT yongyuchang sinrlossanduserselectioninmassivemumisosystemswithzfbf AT tianyizeng sinrlossanduserselectioninmassivemumisosystemswithzfbf AT binwang sinrlossanduserselectioninmassivemumisosystemswithzfbf |
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1724735231129288704 |