Probability Distribution-Based CSI Feedback for Massive MIMO Systems

Youngrok Jang; Taehyoung Kim; Sooyong Choi

doi:10.1109/TVT.2022.3230408

Probability Distribution-Based CSI Feedback for Massive MIMO Systems

Youngrok Jang, Taehyoung Kim, Sooyong Choi

Department of Electrical and Electronic Engineering

Research output: Contribution to journal › Article › peer-review

Abstract

In this paper, a new channel state information (CSI) feedback scheme based on probability distribution is proposed for massive multiple-input multiple-output (MIMO) systems. In the proposed scheme, the real and imaginary parts of the channel elements are divided into several groups and sorted in ascending order. The sorted channel elements are approximated to a cumulative distribution function of a predefined probability distribution, and parameters representing the probability distributions are obtained for each group. The generated CSI, including the representing parameters and original ordering information, is fed back to the base station (BS). Finally, the channel vectors are reconstructed based on the CSI from the BS. It has been verified that the proposed scheme outperforms the conventional CSI feedback schemes in terms of the sum rate under a similar feedback overhead with low computational complexity.

Original language	English
Pages (from-to)	1-6
Number of pages	6
Journal	IEEE Transactions on Vehicular Technology
DOIs	https://doi.org/10.1109/TVT.2022.3230408
Publication status	Accepted/In press - 2022

Bibliographical note

Publisher Copyright:
IEEE

All Science Journal Classification (ASJC) codes

Automotive Engineering
Aerospace Engineering
Electrical and Electronic Engineering
Applied Mathematics

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10.1109/TVT.2022.3230408

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title = "Probability Distribution-Based CSI Feedback for Massive MIMO Systems",

abstract = "In this paper, a new channel state information (CSI) feedback scheme based on probability distribution is proposed for massive multiple-input multiple-output (MIMO) systems. In the proposed scheme, the real and imaginary parts of the channel elements are divided into several groups and sorted in ascending order. The sorted channel elements are approximated to a cumulative distribution function of a predefined probability distribution, and parameters representing the probability distributions are obtained for each group. The generated CSI, including the representing parameters and original ordering information, is fed back to the base station (BS). Finally, the channel vectors are reconstructed based on the CSI from the BS. It has been verified that the proposed scheme outperforms the conventional CSI feedback schemes in terms of the sum rate under a similar feedback overhead with low computational complexity.",

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AU - Jang, Youngrok

AU - Kim, Taehyoung

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PY - 2022

Y1 - 2022

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AB - In this paper, a new channel state information (CSI) feedback scheme based on probability distribution is proposed for massive multiple-input multiple-output (MIMO) systems. In the proposed scheme, the real and imaginary parts of the channel elements are divided into several groups and sorted in ascending order. The sorted channel elements are approximated to a cumulative distribution function of a predefined probability distribution, and parameters representing the probability distributions are obtained for each group. The generated CSI, including the representing parameters and original ordering information, is fed back to the base station (BS). Finally, the channel vectors are reconstructed based on the CSI from the BS. It has been verified that the proposed scheme outperforms the conventional CSI feedback schemes in terms of the sum rate under a similar feedback overhead with low computational complexity.

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Probability Distribution-Based CSI Feedback for Massive MIMO Systems

Abstract

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