# An Energy-Efficient Coverage Algorithm for Macrocell--Small Cell Network Systems
## 5 Results and Discussions
### Effects of the Number of Users on the Various Performance Aspects
In addition, it is found that, at high traffic volumes, power consumption for the proposed algorithm is  
Figure 16: Effect of the number of users on the total power consumption levels of transceivers at all the BSs for the proposed algorithm, SBS-Cell-Enlarged, and SBS-Random. still lower compared to SBS-Cell-Enlarged. In terms of the outage ratio under high traffic volumes, as shown in Figure 15, the proposed algorithm is largely more effective than SBS-Cell-Enlarged. These outcomes indicate that the proposed algorithm allows for adjustments to or the shutting down of SBSs in a smart manner, depending on the number of users and the location distribution of users. Figure 17 demonstrates the effect of the number of users on the average transmission rates of the proposed algorithm, SBS-Cell-Enlarged, and SBS-Random. At low traffic volumes, the average transmission rates of the proposed algorithm are lower than those of SBS-Cell-Enlarged and SBS-Random, but higher than the average required transmission rate due to the efficient configurations of (3)-(8). However, recall that in terms of total power consumption (see Figure 16), the proposed algorithm performs better than SBS-Cell-Enlarged and SBS-Random. Unlike SBS-Cell-Enlarged and SBS-Random, which will always expand SBSs, the proposed algorithm provides users with channels with lower transmission power; as a result, the transmission rate for users is lower. Meanwhile, the rate of SBS-Random is found to be slightly higher than that of SBS-Cell-Enlarged. This is due to the difference in transmission rates caused by the use of channels with the MBS and SBSs (that is, a higher transmission rate can be obtained by using the MBS as compared to any SBS) and the smaller number of available SBSs in SBS-Random when compared to SBS-Cell-Enlarged (implying that SBS-Random has a higher possibility of using the MBS). As the traffic volume increases, the average transmission rate decreases at a slower rate under the proposed algorithm than under SBS-Cell-Enlarged and SBS-Random, and it decreases at the fastest rate under SBS-Random. Due to the smaller quantity of available SBSs and channels in SBS-Random as compared to the other two methods, it increases the likelihood of a user outage at higher traffic volumes, and thus, reduces the average transmission rate. More specifically, it can be seen in Figure 17 that SBS-Random's average transmission rate begins to drop when the traffic volume increases to about 160, whereas the average transmission rates of the proposed algorithm and SBS-Cell-Enlarged do not drop. At a traffic volume of about 240, SBS-Cell-Enlarged's average transmission rate begins to drop due to the occurrence of user outage (see Figure 15). At this volume, it is also found that the average transmission rate drops more substantially under SBS-Random. Only when the proposed algorithm is used does the rate not drop at that traffic volume. When the traffic volume reaches 570, the average transmission rate of the proposed algorithm does decrease, but it still remains higher than the average required transmission rate. This is due to the proposed algorithm's ability to effectively close, open, and scale SBSs, which allows for the effective distribution of each SBS channel to users. Although the average transmission rate of SBS-Cell-Enlarged at this volume is higher than the required value, its power consumption is higher than that of the proposed algorithm. Moreover, one can also see that the average transmission rate of SBS-Random is much lower than the required value. Figure 17: Effect of the number of users on the average transmission rates for the proposed algorithm, SBS-Cell-Enlarged, and SBS-Random.