LMS for truncate CSI feedback in massive MIMO

Ali Almohammedi; Mohamed Deriche

doi:10.1109/iCCECE46942.2019.8941771

LMS for truncate CSI feedback in massive MIMO

Ali Almohammedi
, Mohamed Deriche

Department of Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

In this work, a new methodology for estimation of channel state information (CSI) is presented dependent upon the idea of Least Mean Square (LMS). The strategy is formed to massive MIMO frameworks through feedback communications. The technique is intended to reduce the amount of feedback communication information contains in the CSI data block from the mobile client to the base station. The data amount of encoder at the mobile client side is reduced utilizing the discrete cosine transform (DCT) on the CSI matrix. The retrieved CSI data block toward the base station side employments an IDCT (Inverse DCT) with recreate those CSI matrix. Our simulations indicate better results considering normalized mean-square-error (NMSE) as performance measurement against existing methodologies.

Original language	English
Title of host publication	Proceedings - 2019 International Conference on Computing, Electronics and Communications Engineering, iCCECE 2019
Editors	Mahdi H. Miraz, Peter S. Excell, Andrew Ware, Safeeullah Soomro, Maaruf Ali
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	241-246
Number of pages	6
ISBN (Electronic)	9781728121383
DOIs	https://doi.org/10.1109/iCCECE46942.2019.8941771
State	Published - Aug 2019

Publication series

Name	Proceedings - 2019 International Conference on Computing, Electronics and Communications Engineering, iCCECE 2019

Bibliographical note

Publisher Copyright:
© 2019 IEEE.

Keywords

Channel state information (csi)
Compressed sensing (cs)
Least mean square (lms)
Massive mimo
Reconstruction

ASJC Scopus subject areas

Electrical and Electronic Engineering
Control and Optimization
Health Informatics
Artificial Intelligence
Computer Networks and Communications
Computer Science Applications
Hardware and Architecture

Access to Document

10.1109/iCCECE46942.2019.8941771

Cite this

Almohammedi, A., & Deriche, M. (2019). LMS for truncate CSI feedback in massive MIMO. In M. H. Miraz, P. S. Excell, A. Ware, S. Soomro, & M. Ali (Eds.), Proceedings - 2019 International Conference on Computing, Electronics and Communications Engineering, iCCECE 2019 (pp. 241-246). Article 8941771 (Proceedings - 2019 International Conference on Computing, Electronics and Communications Engineering, iCCECE 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/iCCECE46942.2019.8941771

Almohammedi, Ali ; Deriche, Mohamed. / LMS for truncate CSI feedback in massive MIMO. Proceedings - 2019 International Conference on Computing, Electronics and Communications Engineering, iCCECE 2019. editor / Mahdi H. Miraz ; Peter S. Excell ; Andrew Ware ; Safeeullah Soomro ; Maaruf Ali. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 241-246 (Proceedings - 2019 International Conference on Computing, Electronics and Communications Engineering, iCCECE 2019).

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abstract = "In this work, a new methodology for estimation of channel state information (CSI) is presented dependent upon the idea of Least Mean Square (LMS). The strategy is formed to massive MIMO frameworks through feedback communications. The technique is intended to reduce the amount of feedback communication information contains in the CSI data block from the mobile client to the base station. The data amount of encoder at the mobile client side is reduced utilizing the discrete cosine transform (DCT) on the CSI matrix. The retrieved CSI data block toward the base station side employments an IDCT (Inverse DCT) with recreate those CSI matrix. Our simulations indicate better results considering normalized mean-square-error (NMSE) as performance measurement against existing methodologies.",

keywords = "Channel state information (csi), Compressed sensing (cs), Least mean square (lms), Massive mimo, Reconstruction",

author = "Ali Almohammedi and Mohamed Deriche",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.",

year = "2019",

month = aug,

doi = "10.1109/iCCECE46942.2019.8941771",

language = "English",

series = "Proceedings - 2019 International Conference on Computing, Electronics and Communications Engineering, iCCECE 2019",

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pages = "241--246",

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address = "United States",

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Almohammedi, A & Deriche, M 2019, LMS for truncate CSI feedback in massive MIMO. in MH Miraz, PS Excell, A Ware, S Soomro & M Ali (eds), Proceedings - 2019 International Conference on Computing, Electronics and Communications Engineering, iCCECE 2019., 8941771, Proceedings - 2019 International Conference on Computing, Electronics and Communications Engineering, iCCECE 2019, Institute of Electrical and Electronics Engineers Inc., pp. 241-246. https://doi.org/10.1109/iCCECE46942.2019.8941771

LMS for truncate CSI feedback in massive MIMO. / Almohammedi, Ali; Deriche, Mohamed.
Proceedings - 2019 International Conference on Computing, Electronics and Communications Engineering, iCCECE 2019. ed. / Mahdi H. Miraz; Peter S. Excell; Andrew Ware; Safeeullah Soomro; Maaruf Ali. Institute of Electrical and Electronics Engineers Inc., 2019. p. 241-246 8941771 (Proceedings - 2019 International Conference on Computing, Electronics and Communications Engineering, iCCECE 2019).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Deriche, Mohamed

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AB - In this work, a new methodology for estimation of channel state information (CSI) is presented dependent upon the idea of Least Mean Square (LMS). The strategy is formed to massive MIMO frameworks through feedback communications. The technique is intended to reduce the amount of feedback communication information contains in the CSI data block from the mobile client to the base station. The data amount of encoder at the mobile client side is reduced utilizing the discrete cosine transform (DCT) on the CSI matrix. The retrieved CSI data block toward the base station side employments an IDCT (Inverse DCT) with recreate those CSI matrix. Our simulations indicate better results considering normalized mean-square-error (NMSE) as performance measurement against existing methodologies.

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BT - Proceedings - 2019 International Conference on Computing, Electronics and Communications Engineering, iCCECE 2019

A2 - Miraz, Mahdi H.

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Almohammedi A, Deriche M. LMS for truncate CSI feedback in massive MIMO. In Miraz MH, Excell PS, Ware A, Soomro S, Ali M, editors, Proceedings - 2019 International Conference on Computing, Electronics and Communications Engineering, iCCECE 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 241-246. 8941771. (Proceedings - 2019 International Conference on Computing, Electronics and Communications Engineering, iCCECE 2019). doi: 10.1109/iCCECE46942.2019.8941771

LMS for truncate CSI feedback in massive MIMO

Abstract

Publication series

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this