An Overview of Enabling Green Cellular Networks
Keywords:
Cellular Networks, Energy Consumption, Energy Efficiency (EE), Green Metrics, LTE.Abstract
For the last few 70 years, phone systems have completely changed how users control network connections, but they actually needed a meaningful effort and time from drivers to advance a technology modems that was developed with low deployment costs, widespread coverage, and customer satisfaction attacks in mind. Because of their large energy consumption, traditional "macro" Base Stations (BSs) have proved to be insignificant in terms of running costs in the past. Green communication is becoming one of the key design goals for future mobile networks, and current research is targeted at allowing long-term development of wireless data equipment. Several approaches to enhancing the efficiency of wireless devices have really been proposed so far. Small cells with low-cost, minimal Access Points (APs)hold promise for limiting emission power and improving spectral efficiency. By adjusting network settings to load changes while meeting quality requirements, dynamic radio resource management may minimize energy waste. APs can adjust their operating points to changing circumstances thanks to flexible hardware platforms. This survey makes a three-fold contribution. We examine the literature-based methods for evaluating modern wireless platform's energy usage There are examples of green performance measure and have been used and potential export that have also been considered. Finally, basing on a hypothesized category, we describe and critically assess energy conservation accelerators recently offered by the telecom community.
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References
S. Committee, IEEE Standard for Software Verification and Validation IEEE Standard for Software Verification and Validation. 1998.
L. C. Wang and S. Rangapillai, “A survey on green 5G cellular networks,” in 2012 International Conference on Signal Processing and Communications, SPCOM 2012, 2012.
S. D. Verifier and A. H. Drive, “Simulink ® Verification and Validation TM Reference,” ReVision, 2015.
P. V. Klaine, M. A. Imran, O. Onireti, and R. D. Souza, “A Survey of Machine Learning Techniques Applied to Self-Organizing Cellular Networks,” IEEE Communications Surveys and Tutorials. 2017.
Y. He, F. R. Yu, N. Zhao, H. Yin, H. Yao, and R. C. Qiu, “Big Data Analytics in Mobile Cellular Networks,” IEEE Access, 2016.
Y. Zhang, “A foundation for the design and analysis of robotic systems and behaviors,” 1994.
M. Bobaru, M. Borges, M. d’Amorim, and C. S. Păsăreanu, NASA formal methods : third international symposium, NFM 2011, Pasadena, CA, USA, April 18-20, 2011 : proceedings. 2011.
A. Asadi, Q. Wang, and V. Mancuso, “A survey on device-to-device communication in cellular networks,” IEEE Commun. Surv. Tutorials, 2014.
H. ElSawy, A. Sultan-Salem, M. S. Alouini, and M. Z. Win, “Modeling and Analysis of Cellular Networks Using Stochastic Geometry: A Tutorial,” IEEE Commun. Surv. Tutorials, 2017.
Y. Zaki, T. Pötsch, J. Chen, L. Subramanian, and C. Görg, “Adaptive Congestion Control for Unpredictable Cellular Networks,” Comput. Commun. Rev., 2015.
S. Losacker, “The geography of green technology licensing in China,” Reg. Stud. Reg. Sci., 2020. [12]L. Desheng, C. Jiakui, and Z. Ning, “Political connections and green technology innovations under an environmental regulation,” J. Clean. Prod., 2021. [13]W. Lisi, R. Zhu, and C. Yuan, “Embracing green innovation via green supply chain learning: The moderating role of green technology turbulence,” Sustain. Dev., 2020.
J. Jiao, C. Chen, and Y. Bai, “Is green technology vertical spillovers more significant in mitigating carbon intensity? Evidence from Chinese industries,” J. Clean. Prod., 2020.
Y. Ma, Q. Zhang, and Q. Yin, “Top management team faultlines, green technology innovation and firm financial performance,” J. Environ. Manage., 2021.
M. Yi, X. Fang, L. Wen, F. Guang, and Y. Zhang, “The heterogeneous effects of different environmental policy instruments on green technology innovation,” Int. J. Environ. Res. Public Health, 2019.
S. Arora and S. Saraswat, “Vermifiltration as a natural, sustainable and green technology for environmental remediation: A new paradigm for wastewater treatment process,” Curr. Res. Green Sustain. Chem., 2021.
S. Wang, Y. Cheng, X. Zhang, and C. Zhu, “The implications of vertical strategic interaction on green technology investment in a supply chain,” Sustain., 2020.
Q. Guo, M. Zhou, N. Liu, and Y. Wang, “Spatial effects of environmental regulation and green credits on green technology innovation under low-carbon economy background conditions,” Int. J. Environ. Res. Public Health, 2019.
D. Xia, W. Chen, Q. Gao, R. Zhang, and Y. Zhang, “Research on enterprises’ intention to adopt green technology imposed by environmental regulations with perspective of state ownership,” Sustain., 2021.
J. Hu, Z. Wang, Q. Huang, and X. Zhang, “Environmental regulation intensity, foreign direct investment, and green technology Spillover-An empirical study,” Sustain., 2019.
B. Forés, “Beyond gathering the ‘low-hanging fruit’ of green technology for improved environmental performance: An empirical examination of the moderating effects of proactive environmental management and business strategies,” Sustain., 2019.
S. Zhu and A. Ye, “Does the impact of China’s Outward Foreign Direct Investment on reverse green technology process differ across countries?,” Sustain., 2018.
J. Zhang et al., “Understanding the impact of environmental regulations on green technology
innovation efficiency in the construction industry,” Sustain. Cities Soc., 2021.
T. Stucki and M. Woerter, “The private returns to knowledge: A comparison of ICT, biotechnologies, nanotechnologies, and green technologies,” Technol. Forecast. Soc. Change, 2019.