Abstract
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.
Highlights
The advancement in the Internet of Things (IoT) technology enables a huge amount of low-energy consuming devices to be deployed for different applications and services
In the considered radio access network (RAN), we assume 20 MHz system bandwidth with 10 RBs and 6 randomly distributed user equipment (UE) that are associated with the remote radio heads (RRHs)
We assume 3 randomly distributed RRHs and an high-power node (HPN) which are separated from the UEs at propagation distance d
Summary
The advancement in the Internet of Things (IoT) technology enables a huge amount of low-energy consuming devices to be deployed for different applications and services. Wireless networks consume excessive energy and emit considerable carbon dioxide (CO2). This is even more challenging in the off-grid sites [1]. Its implementation brings about an upsurge in power consumption [5] This can be attributed to the huge number of the required BSs. It is noteworthy that BSs consume most of the network energy [6, 7]. To improve the network EE, both academia and industry are focusing on green communications [6–8] In this context, certain consortiums and projects such as the Green-Touch, Green-IT, and Green Radio project have been focusing on the wireless network’s energy consumption and carbon emission reduction through the development of advanced green radio architectures and techniques [7, 9].
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