Energy-Based Cell Association in Nonuniform Renewable Energy-Powered Cellular Networks: Analysis and Optimization of Carbon Efficiency

IF 7.9 2区计算机科学 Q1 ENGINEERING, MULTIDISCIPLINARY

IEEE Transactions on Network Science and Engineering Pub Date : 2025-04-28 DOI:10.1109/TNSE.2025.3565065

Yuxi Zhao;Vicente Casares-Giner;Vicent Pla;Luis Guijarro;Iztok Humar;Yi Zhong;Xiaohu Ge

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Abstract

The increasing global push for carbon reduction highlights the importance of integrating renewable energy into the supply chain of cellular networks. However, due to the stochastic nature of renewable energy generation and the uneven load distribution across base stations, the utilization rate of renewable energy remains low. To address these challenges, this paper investigates the trade-off between carbon emissions and downlink throughput in cellular networks, offering insights into optimizing both network performance and sustainability. The renewable energy state of base station batteries and the number of occupied channels are modeled as a quasi-birth-death process. We construct models for the probability of channel blocking, average successful transmission probability for users, downlink throughput, carbon emissions, and carbon efficiency based on stochastic geometry. Based on these analyses, an energy-based cell association scheme is proposed to optimize the carbon efficiency of cellular networks. The results show that, compared to the closest cell association scheme, the energy-based cell association scheme is capable of reducing the carbon emissions of the network by 13.0% and improving the carbon efficiency by 11.3%.

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非均匀可再生能源驱动的蜂窝网络中基于能量的细胞关联：碳效率分析与优化

全球对碳减排的推动越来越大，这凸显了将可再生能源整合到蜂窝网络供应链中的重要性。然而，由于可再生能源发电的随机性和各基站负荷分布的不均匀性，可再生能源的利用率仍然很低。为了应对这些挑战，本文研究了蜂窝网络中碳排放和下行链路吞吐量之间的权衡，为优化网络性能和可持续性提供了见解。将基站电池的可再生能源状态和信道占用数建模为一个准生-死过程。我们构建了基于随机几何的信道阻塞概率、用户平均成功传输概率、下行链路吞吐量、碳排放和碳效率模型。在此基础上，提出了一种基于能量的小区关联方案，以优化小区网络的碳效率。结果表明，与最接近的细胞关联方案相比，基于能量的细胞关联方案能够使网络的碳排放量减少13.0%，碳效率提高11.3%。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Transactions on Network Science and Engineering Engineering-Control and Systems Engineering

CiteScore

12.60

自引率

9.10%

发文量

393

期刊介绍： The proposed journal, called the IEEE Transactions on Network Science and Engineering (TNSE), is committed to timely publishing of peer-reviewed technical articles that deal with the theory and applications of network science and the interconnections among the elements in a system that form a network. In particular, the IEEE Transactions on Network Science and Engineering publishes articles on understanding, prediction, and control of structures and behaviors of networks at the fundamental level. The types of networks covered include physical or engineered networks, information networks, biological networks, semantic networks, economic networks, social networks, and ecological networks. Aimed at discovering common principles that govern network structures, network functionalities and behaviors of networks, the journal seeks articles on understanding, prediction, and control of structures and behaviors of networks. Another trans-disciplinary focus of the IEEE Transactions on Network Science and Engineering is the interactions between and co-evolution of different genres of networks.