# How Trend of Increasing Data Volume Affects the Energy Efficiency of 5G Networks
## 6 Simulation of 5G RAN Deployment and Operation Approaches  
MNOs can exploit different approaches for the initial deployment of new BSs in 5G RANs. However, the selection of the best 5G network deployment approach in terms of keeping network EE at optimal levels is still an open question to MNOs. As in the case of previous generations of the cellular networks, implementation of the 5G network can last for years until full deployment in terms of needed capacity and coverage on the national level of complete countries will be achieved. According to the prediction in Reference [1], it is expected that 60% of the world population will be covered with 5G signal by 2026. By that period, installed 5G RAN resources will also need to accommodate increased DVs, which will be significantly higher than the ones at the first years of 2020s. \begin{table}
\begin{tabular}{c c c} \hline \hline
**BS Parameter** & **5G Macro BS** & **5G Small BS** \\ \hline Spectral efficiency (bit/s/Hz/cell) & 10 & 6 \\ \hline Channel bandwidth (MHz) & 100 & 800 \\ \hline Number of sectors (cells)/ BS capacity (Gbit/s) & 3/3 & 1/4.8 \\ \hline Average power consumption in sleep mode (W) & N/A & 5 \\ \hline Average power consumption in active mode (W) & 2000 & 50 \\ \hline Average power consumption in Tx power & & \\ scaling mode (W) & 1600 & 40 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Operating parameters of different BS types used in the analyses. However, different deployment approaches of BSs in 5G RANs can be realized through versatile deployment and RRM techniques. They can have a different long-term impacts on the EC of the RAN. Selecting an appropriate deployment and RRM approach in terms of EE can contribute to the reduction of network EC and consequently to the improvement of the EE metrics. Hence, further analyses reveal how different 5G RAN deployment approaches and continuous increase of DVs in the 2020s influence the 5G network EE metrics. As the largest share of the 5G network EC is related to the EC of BSs in 5G RAN [6], further analyses are performed only for deployment and RRM approaches related to 5G BSs only. Due to the known fact that many active BSs are lightly loaded for most of their operating time, during which active BSs consume energy [3], analyzed deployment and RRM approaches exploit this fact for potential energy savings. More specifically, an operating strategy based on the switching of small BSs in sleep operation mode during the idle traffic periods is considered in the analyses [14; 15]. This operating strategy is considered, since the radio resource scaling (in terms of BS transmit (Tx) power levels, number of active transceivers, number of active subcarriers, etc.) according to dynamics of the user's activity has been proven as an approach that contributes to enhancement of the HetNets EE [4; 5; 16]. Such concepts dedicated to improving BSs EE are included in some contemporary types of the 5G small BSs [17], and even more advanced concepts will be implemented in the future releases of 5G BSs. Three different 5G BSs modes of operation are analyzed in the paper. In Table 2, instant average power consumption of those operation modes, which can be active, sleep and Tx power scaling, are presented. The power consumption of 5G BSs in active, sleep and Tx power scaling modes were selected for analyses based on Reference [3]. The selected BSs power consumption and configuration parameters presented in Table 2 are inherent to the preliminary models of 5G small and macro BSs. The power consumption of BS working in active mode represents the average power consumption of BS for which operating capacities are fully exploited at the highest Tx powers [3]. The average EC of the small BSs in sleep mode is estimated to be 10% of the average EC characteristic for small BS operating in full active mode (Table 2). Due to the necessity of ensuring constant coverage of the area with 5G signal, the possibility that macro BSs can be in sleep mode is not considered in the analyses (Table 2).