Efficient MIMO PHY Abstraction With Imperfect CSI for Fast Simulations

Liu Cao; Lyutianyang Zhang; Sian Jin; Sumit Roy

doi:10.1109/LWC.2022.3233542

Efficient MIMO PHY Abstraction With Imperfect CSI for Fast Simulations

Liu Cao^*
, Lyutianyang Zhang
, Sian Jin
, Sumit Roy

^*此作品的通讯作者

University of Washington
Princeton University

科研成果: 期刊稿件 › 文章 › 同行评审

4 引用（Scopus）

摘要

This letter continues our prior work in Jin et al. (2021) on efficient PHY layer abstractions for scaling link simulations for complex scenarios to include the essential real-world impact of imperfect channel estimation. We extend the EESM-log-SGN abstraction by incorporating a model for effective SINR including channel estimation error, for multiple-input and multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) configurations, tailored towards IEEE 802.11ac/ax networks. The developed methods are then validated under different MIMO configurations for subsequent inclusion in ns-3 (www.nsnam.org) based cross-layer network performance evaluation.

源语言	英语
页（从-至）	530-534
页数	5
期刊	IEEE Wireless Communications Letters
卷	12
期	3
DOI	https://doi.org/10.1109/LWC.2022.3233542
出版状态	已出版 - 1 3月 2023
已对外发布	是

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title = "Efficient MIMO PHY Abstraction With Imperfect CSI for Fast Simulations",

abstract = "This letter continues our prior work in Jin et al. (2021) on efficient PHY layer abstractions for scaling link simulations for complex scenarios to include the essential real-world impact of imperfect channel estimation. We extend the EESM-log-SGN abstraction by incorporating a model for effective SINR including channel estimation error, for multiple-input and multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) configurations, tailored towards IEEE 802.11ac/ax networks. The developed methods are then validated under different MIMO configurations for subsequent inclusion in ns-3 (www.nsnam.org) based cross-layer network performance evaluation.",

keywords = "EESM-log-SGN, MMSE receiver, PHY layer abstraction, link-to-system (L2S)",

author = "Liu Cao and Lyutianyang Zhang and Sian Jin and Sumit Roy",

note = "Publisher Copyright: {\textcopyright} 2012 IEEE.",

year = "2023",

month = mar,

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doi = "10.1109/LWC.2022.3233542",

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AU - Cao, Liu

AU - Zhang, Lyutianyang

AU - Jin, Sian

AU - Roy, Sumit

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Y1 - 2023/3/1

N2 - This letter continues our prior work in Jin et al. (2021) on efficient PHY layer abstractions for scaling link simulations for complex scenarios to include the essential real-world impact of imperfect channel estimation. We extend the EESM-log-SGN abstraction by incorporating a model for effective SINR including channel estimation error, for multiple-input and multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) configurations, tailored towards IEEE 802.11ac/ax networks. The developed methods are then validated under different MIMO configurations for subsequent inclusion in ns-3 (www.nsnam.org) based cross-layer network performance evaluation.

AB - This letter continues our prior work in Jin et al. (2021) on efficient PHY layer abstractions for scaling link simulations for complex scenarios to include the essential real-world impact of imperfect channel estimation. We extend the EESM-log-SGN abstraction by incorporating a model for effective SINR including channel estimation error, for multiple-input and multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) configurations, tailored towards IEEE 802.11ac/ax networks. The developed methods are then validated under different MIMO configurations for subsequent inclusion in ns-3 (www.nsnam.org) based cross-layer network performance evaluation.

KW - EESM-log-SGN

KW - MMSE receiver

KW - PHY layer abstraction

KW - link-to-system (L2S)

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VL - 12

SP - 530

EP - 534

JO - IEEE Wireless Communications Letters

JF - IEEE Wireless Communications Letters

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Efficient MIMO PHY Abstraction With Imperfect CSI for Fast Simulations

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