4.4 Article

Towards a Sustainable Green Design for Next-Generation Networks

期刊

WIRELESS PERSONAL COMMUNICATIONS
卷 121, 期 2, 页码 1123-1138

出版社

SPRINGER
DOI: 10.1007/s11277-021-09062-2

关键词

5G; 6G; Cloud RAN; Dense networks; Energy efficiency; Energy harvesting; Green communications; Green energy; Power consumption; Wireless network

资金

  1. European Regional Development Fund (FEDER), through the Regional Operational Programme of Lisbon (POR LISBOA 2020) [POCI-01-0247-FEDER-024539, CENTRO-01-0145-FEDER-000010, POCI-01-0145-FEDER-016432]
  2. Competitiveness and Internationalization Operational Programme (COMPETE 2020) of the Portugal 2020 (P2020) [POCI-01-0247-FEDER-024539, CENTRO-01-0145-FEDER-000010, POCI-01-0145-FEDER-016432]
  3. FEDER through COMPETE 2020 of the P2020 [POCI-01-0145-FEDER-029405, UIDB/50008/2020-UIDP/50008/2020]

向作者/读者索取更多资源

The paper discusses the excessive energy consumption and carbon dioxide emission in wireless networks, with a focus on energy efficiency and green communications in mobile networks. By reviewing various energy efficiency improvement techniques and considering a hybrid model, an energy-efficient power allocation algorithm is proposed to support the energy demand of wireless networks.
The evolution in the Information and Communications Technologies industry results in excessive energy consumption and carbon dioxide emission in the wireless networks. In this context, energy efficiency in mobile networks has been attracting considerable attention as green communications and operational expenditures reduction depend on it. Although the Internet of Things is to be supported by devices that are low-energy consuming, the power consumption of the huge number to be connected for several applications and services demand significant attention. To offer insights into green communications, this paper reviews various energy efficiency improvement techniques. Also, we consider a hybrid model in which the main grid power and dynamically harvested green energy from renewable energy sources can be leveraged to support the energy demand of the radio access network. In this regard, we reformulate the energy consumption model and consider an energy-efficient power allocation algorithm for green energy optimization. Numerical results show that with resource allocation algorithm exploitation, the energy efficiency can be enhanced. Besides, the amount of the grid energy consumption can be considerably minimized, resulting in the greenhouse gas emissions reduction in the wireless networks.

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