Channel state information acquisition algorithm based on deep learning for IoT

To solve the problem of high feedback overhead when the user sends channel state information (CSI) to the base station in massive multiple input multiple output (MIMO) based on Internet of things system,a CSI feedback network based on deep learning was proposed to feedback CSI.Firstly,the proposed n...

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Main Authors: Yong LIAO, Haimei YAO, Yuanxiao HUA
Format: Article
Language:zho
Published: China InfoCom Media Group 2019-03-01
Series:物联网学报
Subjects:
Online Access:http://www.wlwxb.com.cn/zh/article/doi/10.11959/j.issn.2096-3750.2019.00085/
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author Yong LIAO
Haimei YAO
Yuanxiao HUA
author_facet Yong LIAO
Haimei YAO
Yuanxiao HUA
author_sort Yong LIAO
collection DOAJ
description To solve the problem of high feedback overhead when the user sends channel state information (CSI) to the base station in massive multiple input multiple output (MIMO) based on Internet of things system,a CSI feedback network based on deep learning was proposed to feedback CSI.Firstly,the proposed network used convolutional neural network (CNN) to extract channel feature vectors and maxpooling to compress the data.Then the compressed CSI was decompressed by using full connection and CNN to restore the original channel.The simulation results show that compared with the existing CSI feedback methods,the CSI recovered by the proposed CSI feedback network is closer to the original channel,and the reconstruction quality is improved significantly.
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id doaj-art-a6c2238db1444fd8b94a104413233d92
institution Kabale University
issn 2096-3750
language zho
publishDate 2019-03-01
publisher China InfoCom Media Group
record_format Article
series 物联网学报
spelling doaj-art-a6c2238db1444fd8b94a104413233d922025-01-15T02:52:19ZzhoChina InfoCom Media Group物联网学报2096-37502019-03-01381359644039Channel state information acquisition algorithm based on deep learning for IoTYong LIAOHaimei YAOYuanxiao HUATo solve the problem of high feedback overhead when the user sends channel state information (CSI) to the base station in massive multiple input multiple output (MIMO) based on Internet of things system,a CSI feedback network based on deep learning was proposed to feedback CSI.Firstly,the proposed network used convolutional neural network (CNN) to extract channel feature vectors and maxpooling to compress the data.Then the compressed CSI was decompressed by using full connection and CNN to restore the original channel.The simulation results show that compared with the existing CSI feedback methods,the CSI recovered by the proposed CSI feedback network is closer to the original channel,and the reconstruction quality is improved significantly.http://www.wlwxb.com.cn/zh/article/doi/10.11959/j.issn.2096-3750.2019.00085/massive MIMOinternet of thingsCSI feedbackdeep learning
spellingShingle Yong LIAO
Haimei YAO
Yuanxiao HUA
Channel state information acquisition algorithm based on deep learning for IoT
物联网学报
massive MIMO
internet of things
CSI feedback
deep learning
title Channel state information acquisition algorithm based on deep learning for IoT
title_full Channel state information acquisition algorithm based on deep learning for IoT
title_fullStr Channel state information acquisition algorithm based on deep learning for IoT
title_full_unstemmed Channel state information acquisition algorithm based on deep learning for IoT
title_short Channel state information acquisition algorithm based on deep learning for IoT
title_sort channel state information acquisition algorithm based on deep learning for iot
topic massive MIMO
internet of things
CSI feedback
deep learning
url http://www.wlwxb.com.cn/zh/article/doi/10.11959/j.issn.2096-3750.2019.00085/
work_keys_str_mv AT yongliao channelstateinformationacquisitionalgorithmbasedondeeplearningforiot
AT haimeiyao channelstateinformationacquisitionalgorithmbasedondeeplearningforiot
AT yuanxiaohua channelstateinformationacquisitionalgorithmbasedondeeplearningforiot