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

被引:0
作者
Huang, Yige [1 ]
Jiang, Yanxiang [1 ]
Zheng, Fu-Chun [1 ,2 ]
Zhu, Pengcheng [1 ]
Quek, Tony Q. S. [3 ]
机构
[1] Southeast Univ, Natl Mobile Commun Res Lab, Nanjing 210096, Peoples R China
[2] Harbin Inst Technol, Sch Elect & Informat Engn, Shenzhen 518055, Peoples R China
[3] Singapore Univ Technol & Design, Dept Informat Syst Technol & Design, Singapore 487372, Singapore
基金
中国国家自然科学基金; 新加坡国家研究基金会;
关键词
Ultra reliable low latency communication; Delays; Reliability; Quality of service; Energy efficiency; Resource management; Reliability theory; Uplink; Measurement; Signal to noise ratio; Cell-Free massive MIMO; URLLC; energy efficiency; finite blocklength communications; stochastic network calculus; FREE MASSIVE MIMO; RESOURCE-ALLOCATION; STATISTICAL DELAY; POWER ALLOCATION; ENABLED URLLC; NETWORKS; OPTIMIZATION; PERFORMANCE; DESIGN; ACCESS;
D O I
10.1109/TWC.2024.3519587
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
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.
引用
收藏
页码:2279 / 2296
页数:18
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