## 4 Numerical Results  
In this section, we compare the performance of the proposed energy saving scheme with that of conventional energy saving schemes in both basic and modified separation architecture. Table 3 shows simulation parameters assumed in numerical results. According to the literature, various values are assumed as the power consumption of sleep mode, such as 1% [73], 15% [13], and 50% [74] of fixed power consumption. In Table 3, we assumed this value as 25% by approximately averaging the reference values. Also, we assumed the switching power between on and off states as the 2.5 times of fixed power consumption using the similar rationale of that in [75] and the switching power between on and _sleep_ states as the 2.5 times of power consumption of _sleep_ state similarly. The parameter values assumed in the simulation of particle swarm optimization is summarized as in Table 4.  
For numerical examples, we obtained energy consumption due to traffic processing, energy consumption due to state switching, total energy consumption, average delay for varying number of UEs, ratio of high rate data, and service time of traffic. There are three schemes, i.e., basic separation, modified separation, and proposed energy saving schemes. In the basic separation scheme, the conventional energy saving scheme is applied in the basic separation architecture. In the modified separation scheme, conventional energy saving scheme is applied in the modified separation architecture. In the proposed energy saving scheme, the proposed energy saving scheme is applied in the modified separation architecture. Figures 9-11 show the energy consumption of BSs due to traffic processing, energy consumption of BSs due to state switching, and total energy consumption of BS by varying the number of UEs. As shown in Figure 9, the energy consumptions of three schemes increase as the number of UEs increases, since traffic load and the number of SBSs in _on_ state increase. The basic separation scheme has the largest energy consumption since low rate data traffic is managed by SBSs and thus more SBSs should be awake. The proposed energy saving scheme has slightly lower energy consumption than the modified separation scheme, since the proposed energy saving scheme can reduce the number of SBSs in _on_ state by efficiently putting SBSs into _sleep_ state. As shown in Figure 10, the proposed energy saving scheme has the smallest energy consumption for most values of the number of UEs \begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Value** \\ \hline PSO iteration & 200 \\ number of swarm & 5 \\ \(v_{max}\) & 4 \\ \(v_{min}\) & \(-4\) \\ \(c_{1}\) & 0.5 \\ \(c_{2}\) & 0.5 \\ \(r_{1}\) & 0.5 \\ \(r_{2}\) & 0.5 \\ \(v_{g}\) & 0.25 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Parameters for particle swarm optimization (PSO). \begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Value** \\ \hline simulation time & 24 h \\ number of SBSs & 50 \\ number of UEs & 250 \\ service time of traffic & UU\(0,2.51\) min \\ inter-arrival time of traffic & U\(\$\)[5, 10] min \\ ratio of high data & 0.5 \\ speed of UE & U\(\$\)[0, 100] km/h \\ \(p_{g}^{f}\) & 21.6 W \\ \(p_{g,x}^{b}\) & 5.4 W \\ \(p_{g,x}^{f}\) & 27 W \\ \(p_{g,x}^{f}\) & 780 W \\ \(r_{g,x}^{b}\) & 1350 W \\ \(P_{aa-off}\) & 54 W \\ \(P_{aa-disp}\) & 13.5 W \\ \(C_{b}\) & 1 Mbps \\ \(C_{b,x}^{f}\) & 0.01 Mbps \\ \(C_{b,x}^{b}\) & 25 Mbps \\ \(C_{b,x}^{b}\) & 500 Mbps \\ \(p_{g,x}^{b}\) & 1.3 W \\ \(p_{g,x}^{b}\) & 120 W \\ \(p_{g,x}^{b}\) & 4.15 W/Mbps \\ \(p_{g}^{M}\) & 4.5 W/Mbps \\ \(T_{aa-off}\) & 0.532 s \\ \(T_{aa-slap}\) & 0.00216 s \\ \(T_{c}\) & 0.05 s \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Simulation parameters. since the state of SBSs in the proposed scheme changes between _on_ and _sleep_ states, which has the smaller energy consumption due to state switching than the transition between _on_ and _off_ states.