Abstract
As the rapid growth of mobile users and Internet-of-Everything devices will continue in the upcoming decade, more and more network capacity will be needed to accommodate such a constant increase in data volumes (DVs). To satisfy such a vast DV increase, the implementation of the fifth-generation (5G) and future sixth-generation (6G) mobile networks will be based on heterogeneous networks (HetNets) composed of macro base stations (BSs) dedicated to ensuring basic signal coverage and capacity, and small BSs dedicated to satisfying capacity for increased DVs at locations of traffic hotspots. An approach that can accommodate constantly increasing DVs is based on adding additional capacity in the network through the deployment of new BSs as DV increases. Such an approach represents an implementation challenge to mobile network operators (MNOs), which is reflected in the increased power consumption of the radio access part of the mobile network and degradation of network energy efficiency (EE). In this study, the impact of the expected increase of DVs through the 2020s on the EE of the 5G radio access network (RAN) was analyzed by using standardized data and coverage EE metrics. An analysis was performed for five different macro and small 5G BS implementation and operation scenarios and for rural, urban, dense-urban and indoor-hotspot device density classes (areas). The results of analyses reveal a strong influence of increasing DV trends on standardized data and coverage EE metrics of 5G HetNets. For every device density class characterized with increased DVs, we here elaborate on the process of achieving the best and worse combination of data and coverage EE metrics for each of the analyzed 5G BSs deployment and operation approaches. This elaboration is further extended on the analyses of the impact of 5G RAN instant power consumption and 5G RAN yearly energy consumption on values of standardized EE metrics. The presented analyses can serve as a reference in the selection of the most appropriate 5G BS deployment and operation approach, which will simultaneously ensure the transfer of permanently increasing DVs in a specific device density class and the highest possible levels of data and coverage EE metrics.
Highlights
This improvement is a consequence of the fact that higher amounts of data will be transferred for the same unit of energy consumption of the base stations (BSs) in the 5G radio access network (RAN)
Obtained results show that an increase in data volumes (DVs) has an opposite effect on data and coverage EE metric of every device density class
This opposite trend in changes of data and coverage EE metric, caused by the increase in DV, indicates that there is no optimal amount of DVs in any of the analyzed device density classes for which a combination of both EE metrics will have the highest values
Summary
The trend of constantly increasing the number of mobile users leads to an increase in traffic data volumes (DVs). It is projected that global mobile data traffic will exceed 300 EB per month in 2026 [1]. Communications (mMTC) and non-mMTC connected devices in the fifth-generation (5G). Networks will increase from 165.6 million in 2020 to 3.256 billion in 2030, with a compound annual growth rate (CAGR) of 35% [2]. All 5G connected devices will, by 2030, account for. 13% of the overall number of connected devices (25.4 billion) worldwide [2]. The fourth-generation (4G) mobile networks will remain the dominant mobile access technology
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