# How Trend of Increasing Data Volume Affects the Energy Efficiency of 5G Networks
## 9 Conclusions  
The continuous increase of DVs on the global level caused by an increase in the number of mobile users and the introduction of novel and more bandwidth-demanding applications imposes challenges in deploying energy-efficient 5G networks. These challenges will additionally be contributed to by the fact that heterogeneous 5G networks must be deployed in areas of different device density classes, which will have different increases of DVs during the 2020s. In this work, the influence of constant increase of DV during the 2020s on network EE was analyzed. The analysis was performed for different 5G network deployment and operation approaches implemented in rural, urban, urban-dense and indoor-hotspot device density classes. The two standardized EE metrics, known as data and coverage EE metrics were used for the assessment of the EE of the proposed 5G BSs deployment and operation approaches. Obtained results show that an increase in 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. Obtained results reveal that only a reduction of 5G network instant power consumption and, consequently, energy consumption, will contribute to the simultaneous improvement of both data and coverage EE metrics. Therefore, the obtained results confirm that only those deployment and operation approaches that implement some of the RRM techniques (such as Tx power scaling and/or putting BSs in sleep mode) can bring the reduction of instant power and energy consumption, thus consequently contributing to the improvement of EE metrics of 5G RANs. Additionally, the presented results indicate that the 5G BSs deployment and operation approaches that have the highest capabilities of adjusting BSs resources according to the increase of DV, will have the highest contribution to the improvement of both EE metrics in any device density class. It is further shown that, for any of the analyzed approaches which exploit adaptation of BSs deployment dynamics and operation activity according to increasing DV trend, the DV increase will cause an increase of the instant power consumption of the 5G network. Therefore, the analyses presented in the paper can serve as a basis in the future processes dedicated to the selection of deployment and operation strategies of 5G networks which will bring the highest network EE metrics, with respect to the permanently increasing DVs in a specific device density class. Our future research activities will be dedicated to the investigation of the impact of DV increase on the 5G network EE of complete countries, which are composed of different in size and proportion device density classes having different DV patterns. Conceptualization, J.L. ; methodology, J.L and Z.K. ; validation, J.L. and Z.K. ; formal analysis, J.L. and Z.K. ; investigation, J.L. and Z.K. ; resources, J.L. and Z.K., data curation, J.L. and Z.K. ; writing--original draft preparation, J.L. and Z.K. ; writing--review and editing, J.L. ; visualization, J.L. and Z.K. ; supervision, J.L. All authors have read and agreed to the published version of the manuscript. This research received no external funding. Not applicable. The authors declare no conflict of interest. The following abbreviations are used in this manuscript.