Performance Analysis of Smart Grids-Oriented C-RAN-URLLC Networks under Unlicensed Spectrum

In this paper, we employ the cloud-radio access network (C-RAN) architecture to support the electricity sensors (ESs) with ultra-reliable and low-latency communication (URLLC) requirements in smart grids. Our study specifically addresses scenarios involving unlicensed spectrum and imperfect channel knowledge, with a focus on evaluating the ESs’ rate performance under listen-before-talk (LST) operations. Utilizing the use-and-then-forget bounding technique in conjunction with finite blocklength capacity theory, we derive a closed-form expression for the achievable rate. This expression facilitates a comprehensive analysis of the impact of LBT across various system configurations. The theoretical findings are validated through extensive simulations, providing significant insights into the performance of ESs in the considered C-RAN-URLLC framework.

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Publication Details

Published
2024-10-18
DOI
https://doi.org/10.1145/3711129.3711204
Primary Topic
Advanced MIMO Systems Optimization
Type
article
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Performance Analysis of Smart Grids-Oriented C-RAN-URLLC Networks under Unlicensed Spectrum

Baoping Ren, Liang Zhu, Minda Shi, Peng Wu et al.
Advanced MIMO Systems Optimization
article

Performance Analysis of Smart Grids-Oriented C-RAN-URLLC Networks under Unlicensed Spectrum

Baoping Ren, Liang Zhu, Minda Shi, Peng Wu, Wei Jiang
article en

Abstract

In this paper, we employ the cloud-radio access network (C-RAN) architecture to support the electricity sensors (ESs) with ultra-reliable and low-latency communication (URLLC) requirements in smart grids. Our study specifically addresses scenarios involving unlicensed spectrum and imperfect channel knowledge, with a focus on evaluating the ESs’ rate performance under listen-before-talk (LST) operations. Utilizing the use-and-then-forget bounding technique in conjunction with finite blocklength capacity theory, we derive a closed-form expression for the achievable rate. This expression facilitates a comprehensive analysis of the impact of LBT across various system configurations. The theoretical findings are validated through extensive simulations, providing significant insights into the performance of ESs in the considered C-RAN-URLLC framework.

North China Electric Power University (CN), Shanghai Electric (China) (CN), China Electric Power Research Institute
Affordable and clean energy
Openalex Percentile: Top 75%
Advanced MIMO Systems Optimization
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Performance Analysis of Smart Grids-Oriented C-RAN-URLLC Networks under Unlicensed Spectrum — Baoping Ren, Liang Zhu, et al. · (2024) | TGRS Research Map | TGRS