# How Trend of Increasing Data Volume Affects the Energy Efficiency of 5G Networks
## 8 Discussion on Performed Analyses and Obtained Results
Nevertheless, the trends of the graphs presenting the impact of DV increase on data and coverage EE metrics will remain for every device density class, as with those in Figures 2-4. Therefore, conclusions presented in this paper about trends in changes of data EE metric, coverage EE metric, instant power and yearly energy consumption caused by an increase in DVs can be generalized for any practical implementation of 5G network segment which belongs to a specific device density class. An additional discussion point is related to the assumption used in the analyses according to which the DV during a single year is constant in the area of every device density class (Table 1). In reality, the instant DVs that must be transferred in the area of every device density class will vary during a day and throughout the year. To approximate these DV variations, DVs used in the analyses represent the average yearly DVs expected to be transferred by the 5G BSs located in a square kilometer area of a specific device density class. They are calculated for every year in the 2020s (Figures 2-4) and for every device density class. The calculation takes into account an increase in the projected number of active user devices through the 2020s and the sum of their minimal uplink and downlink throughputs prescribed by ETSI standard for every device density class [1; 2] Hence, it is reasonable to assume that the DVs used for modeling the effect of DV increase in square kilometer area of every analyzed device density class can be set to fixed DVs. For the purpose of analyses presented in this work, these fixed DVs express an average expected DVs in each year of the 2020s. A final assumption is related to performing analyses with the excluded contribution to the total network energy consumption of other BS site elements, such as backhaul network equipment, cooling equipment and ancillary equipment. Moreover, the contribution to the overall network energy consumption of other types of BSs which can be collocated with 5G BSs at the same BSs site (e.g., 2G, 3G and 4G BSs) is not considered in the analyses. Although the energy consumption of all stated network elements contributes to the overall MN energy consumption and, therefore, impacts the network data and coverage EE metrics, this contribution was excluded from the analyses. The reason for this exclusion is in the main goal of this paper, which is dedicated to enlightening how the expected future increase in DVs will impact standardized data and coverage EE metrics of 5G networks. The analysis is, therefore, performed for 5G networks only, due to the fact that the cellular RAN has the greatest contribution to the overall MN power consumption and 5G networks will be dedicated to transferring the largest shares of DVs in the future transfer of DVs in mobile networks. For that reason, only 5G BSs and corresponding power consumption profiles were considered in the analyses. Therefore, the results of this analysis can be used for developing energy-efficient implementation and operation strategies of BSs in contemporary 5G networks.