# How Trend of Increasing Data Volume Affects the Energy Efficiency of 5G Networks
## 7 Results on the Impact of Increasing DVs on 5G Network EE  
The impacts of the increase in DVs on data and coverage EE metrics of 5G RAN for different device density classes and five deployment approaches are shown in Figure 2a-d. Figure 2a-d indicated estimated DVs for each year during the 2020s, with 2030 as the last year for which DV estimation was performed. According to the presented simulation results, the increase in DVs has a significant impact on data and coverage EE metrics of 5G RANs. This impact is visible for every device density class and deployment approach. In the case of all deployment approaches and for every analyzed device density class, the data EE metric increases with the increase of DV that must be transferred in the 5G network (Figure 2a-d). Thus, an increase in DVs has a positive impact on data EE metrics of 5G networks. This implies that a higher amount of DVs can be transferred per Joule of energy consumed by the network BSs of the same area size. Therefore, the global trend of the constant increase of DVs in 5G networks will result in the improvement of the data EE metric. 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 BSs in the 5G RAN.  
On the other hand, for every device density class and most of the deployment approaches, the coverage EE metric decreases as the DV of the analyzed square kilometer area increases (Figure 1(a)-d). This decrease is not perceived only for deployment Approach 3, which presents the traditional RAN implementation approach lacking any deployment or operational mechanisms dedicated to optimizing BSs energy consumption. In the case of other deployment approaches (Approaches 1, 2, 4 and 5), an increase in DVs has a negative influence on coverage EE metrics. This implies that ensuring the transfer of higher DVs over the same area requires more energy which will be consumed by the network elements (BSs) allocated in this area. Therefore, the global trend of the constant increase of DVs in 5G networks will result in the degradation of the coverage EE metric of the radio access part of the network. This decrease is a consequence of the fact that transferring higher amounts of data in a specific device density class demands an increase in the energy consumption of the BSs in the 5G RAN.  
According to Figure 1(a)-d, an increase in DVs causes the opposite trends in changes of data and coverage EE metrics, where an increase in the data EE metric is followed by a decrease in the coverage EE metric. This is not the case only with deployment Approach 3, due to the above-explained reasons. Hence, there is no optimal 5G BSs deployment approach that can simultaneously contribute to the improvement of both standardized EE metrics. Favoring the data EE metric in terms of transferring higher amounts of DVs  
Figure 1: Impact of DV increase on data and coverage EE metrics for each year during the 2020s for (**a**) indoor-hotspot, (**b**) dense-urban, (**c**) urban and (**d**) rural device density class.  
per unit of consumed energy will be on the cost of the degradation of coverage EE metric, and vice versa. However, to have as much energy-efficient 5G RAN as possible, both EE metrics must be simultaneously optimized in terms of obtaining network deployment and operation, which will have the highest possible data and coverage EE metric. This makes the realization of 5G HetNets in terms of satisfying both standardized EE metrics particularly challenging for MNOs. This challenge arises from the fact that there is no optimal DV around which MNOs should keep the traffic intensity in a specific device density class, for which both EE metrics will have the best possible values.