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在QoS约束下通过集中式和分布式睡眠策略实现异构网络中的能量效率最大化。

Maximizing energy efficiency in HetNets through centralized and distributed sleep strategies under QoS constraint.

作者信息

Shabbir Amna, Rizvi Safdar, Shirazi Muhammad Faizan, Alam Muhammad Mansoor, Su'ud Mazliham Mohd

机构信息

Department of Electronic Engineering, NED University of Engineering and Technology, Karachi, Pakistan.

Faculty of Computer and Information, Multimedia University, Cyberjaya, Malaysia.

出版信息

Sci Rep. 2024 Oct 28;14(1):25839. doi: 10.1038/s41598-024-70714-x.

DOI:10.1038/s41598-024-70714-x
PMID:39468085
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11519487/
Abstract

This research addresses the critical need to optimize the Energy Efficiency (EE) for Ultra-Dense HetNets amid the ever-increasing demands for high-speed data networks. The rapid increase in high-speed devices highlights the urgent necessity for a transformative change in upcoming 5G cellular networks. According to Ericsson's 2022 report, mobile data traffic volume is expected to double by 2027, with mobile video traffic anticipated to rise by nearly 30% each year. In response to these challenges, researchers have identified essential technologies that facilitate 5G networks, including massive Multiple-input-Multiple-output (m-MIMO) systems and HetNets. Although both promise enhanced coverage and throughput, HetNets emerges as a cost-effective solution, surpassing m-MIMO in implementation cost and coverage. However, achieving maximum EE in HetNets necessitates careful consideration of various constraints, including delay, coverage probability, and Signal-to-Interference-plus-Noise Ratio (SINR) thresholds. This research marks a significant milestone in adopting the Distributed Dynamic Opportunistic Sleep Strategy (D-DOSS) approach. The D-DOSS method organizes small clusters throughout the network and evaluates key Quality of Service (QoS) parameters including Energy Utilization Efficiency (EUE), Coverage Probability, Data Throughput, and Success Probability using Monte Carlo simulations. This research analyzes Distributed Sleep (DS) and Centralized Schemes (CS) concerning given QoS parameters. While DS methodologies often exhibit performance trade-offs compared to CS, they provide significant advantages in terms of ease of implementation and management. CS, though representing the most commonly used method in ultra-dense HetNets involves high computational costs that complicate its management. By integrating the D-DOSS and addressing various constraints, this research not only advances HetNet technologies but also makes a significant contribution to optimizing EE while preserving network performance and QoS. The innovative D-DOSS approach offers a promising solution to the challenges of energy efficiency in wireless communication networks and paves the way for future advancements in HetNet deployments. The results and analysis show that D-DOSS effectively addresses the limitations of DS and outperforms existing CS techniques.

摘要

随着对高速数据网络的需求不断增加,本研究致力于满足优化超密集异构网络(HetNets)能源效率(EE)的迫切需求。高速设备的迅速增加凸显了即将到来的5G蜂窝网络进行变革性改变的紧迫性。根据爱立信2022年的报告,预计到2027年移动数据流量将翻一番,移动视频流量预计每年增长近30%。为应对这些挑战,研究人员确定了促进5G网络的关键技术,包括大规模多输入多输出(m-MIMO)系统和异构网络。尽管两者都有望提高覆盖范围和吞吐量,但异构网络是一种经济高效的解决方案,在实施成本和覆盖范围方面超过了m-MIMO。然而,要在异构网络中实现最大能源效率,需要仔细考虑各种约束条件,包括延迟、覆盖概率和信号与干扰加噪声比(SINR)阈值。本研究在采用分布式动态机会睡眠策略(D-DOSS)方法方面迈出了重要的里程碑。D-DOSS方法在整个网络中组织小型集群,并使用蒙特卡罗模拟评估关键服务质量(QoS)参数,包括能源利用效率(EUE)、覆盖概率、数据吞吐量和成功概率。本研究分析了给定QoS参数下的分布式睡眠(DS)和集中式方案(CS)。虽然与CS相比,DS方法通常会出现性能权衡,但它们在实施和管理的简易性方面具有显著优势。CS虽然是超密集异构网络中最常用的方法,但计算成本高,管理复杂。通过整合D-DOSS并解决各种约束条件问题,本研究不仅推动了异构网络技术的发展,而且在保持网络性能和QoS的同时,为优化能源效率做出了重大贡献。创新的D-DOSS方法为无线通信网络中的能源效率挑战提供了一个有前景的解决方案,并为异构网络部署的未来发展铺平了道路。结果和分析表明,D-DOSS有效地解决了DS的局限性,并且优于现有的CS技术。

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