Effective Energy Efficiency of Cell-Free mMIMO Systems for URLLC With Probabilistic Delay Bounds and Finite Blocklength Communications

Ultra-Reliable and Low-Latency Communications (URLLC) is essential for sixth generation communications, with Cell-Free massive Multiple-input-Multiple-Output (CF mMIMO) being a promising architecture to support these demands. This paper addresses the challenge of optimizing energy efficiency in CF mMIMO systems for URLLC, focusing on the probabilistic delay bounds and finite blocklength communications. We propose a theoretical framework that considers tail distributions to evaluate extreme reliability and latency requirements, instead of relying on asymptotic analysis. In particular, a closed-form expression for the signal-to-interference-plus-noise ratio (SINR) distribution is derived, accommodating imperfections in channel state information caused by pilot contamination. Then, the paper also presents a comprehensive reliability analysis, incorporating both delay violation probability and average decoding error probability, utilizing stochastic network calculus for accurate statistical modeling. Finally, an innovative power control algorithm is proposed to maximize effective energy efficiency (EEE), the ratio of the effective data rate to total power consumption, while meeting stringent Quality-of-Service (QoS) constraints and power limits. Extensive simulations validate the theoretical framework and the efficacy of the proposed algorithm, demonstrating its ability to enhance EEE in various scenarios and providing insights into the interplay between EEE, delay, and reliability metrics.

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Publication Details

Journal
IEEE Transactions on Wireless Communications
Published
2024-12-26
DOI
https://doi.org/10.1109/twc.2024.3519587
Citations
9
Primary Topic
Advanced MIMO Systems Optimization
Type
article
Field-Weighted Citation Impact
1.88

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article

Effective Energy Efficiency of Cell-Free mMIMO Systems for URLLC With Probabilistic Delay Bounds and Finite Blocklength Communications

Yige Huang, Yanxiang Jiang, Fu‐Chun Zheng, Tony Q. S. Quek et al.
9 citations
IEEE Transactions on Wireless Communications
Advanced MIMO Systems Optimization
1.88
article

Effective Energy Efficiency of Cell-Free mMIMO Systems for URLLC With Probabilistic Delay Bounds and Finite Blocklength Communications

Yige Huang, Yanxiang Jiang, Fu‐Chun Zheng, Tony Q. S. Quek, Pengcheng Zhu
article en
9 citations

Abstract

Ultra-Reliable and Low-Latency Communications (URLLC) is essential for sixth generation communications, with Cell-Free massive Multiple-input-Multiple-Output (CF mMIMO) being a promising architecture to support these demands. This paper addresses the challenge of optimizing energy efficiency in CF mMIMO systems for URLLC, focusing on the probabilistic delay bounds and finite blocklength communications. We propose a theoretical framework that considers tail distributions to evaluate extreme reliability and latency requirements, instead of relying on asymptotic analysis. In particular, a closed-form expression for the signal-to-interference-plus-noise ratio (SINR) distribution is derived, accommodating imperfections in channel state information caused by pilot contamination. Then, the paper also presents a comprehensive reliability analysis, incorporating both delay violation probability and average decoding error probability, utilizing stochastic network calculus for accurate statistical modeling. Finally, an innovative power control algorithm is proposed to maximize effective energy efficiency (EEE), the ratio of the effective data rate to total power consumption, while meeting stringent Quality-of-Service (QoS) constraints and power limits. Extensive simulations validate the theoretical framework and the efficacy of the proposed algorithm, demonstrating its ability to enhance EEE in various scenarios and providing insights into the interplay between EEE, delay, and reliability metrics.

IEEE Transactions on Wireless CommunicationsVol. 24(3)
Singapore University of Technology and Design (SG), Southeast University (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China
Affordable and clean energy
Openalex Percentile: Top 14%
Advanced MIMO Systems Optimization
1.88
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