# Interference Management in Femtocells by the Adaptive Network Sensing Power Control Technique
## 5 Simulation Results and Discussion  
The simulation carried out in MATLAB is based on the simulation parameter set out in [28] and some selected simulation parameters are listed in Table 1. In this simulation, we used an urban model, a single floor building, as shown in Figure 1. We also used the closed access mode HeNB, one of the favorite access modes of domestic subscribers of femtocell services, where only authorized users have access to the services of the femtocell; the MUE in the vicinity of the femtocell has no access to the femtocell.  
The main aim of power controlling in the HeNB is to uphold the FUE coverage and identify potential downlink throughput, while mitigating the ICI experienced by the nearby macro users. Figure 2 shows the macro user's downlink throughput CDF (Cumulative Distribution Function). The simulation of \"No Power Control\" is carried out as a baseline, when there is no power control technique activated in the femtocell; in other words, the femtocell transmits with the maximal transmit power. The femto user-assisted and macro user-assisted power control techniques have almost identical effects in enhancing the throughput performance of the nearby MUE, whereas the simulation results show that the ANS power control technique has a good tradeoff in reducing interference in the MUE and maintaining the QoS requirement of the femtocell users.  
High downlink transmission power of the femtocell provides good signal quality and better coverage to the FUE, though concurrently it creates massive interference to other cell-edge users. The power control techniques, such as the MUE-assisted power control technique, focus on alleviation of interference to macro users; at the same time, they lessen the femto user's performance. Figure 3 shows that the ANS power control scheme provides the best tradeoff mitigation of interference in cell-edge users and maintains also the necessary QoS of femto users.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Parameters** & **Values/Range** \\ \hline Bandwidth & \(10\ \mathrm{GHz}\) \\ Carrier frequency & \(2\ \mathrm{GHz}\) \\ Transmit power of macrocell & \(43\ \mathrm{dBm}\) \\ Transmit power of femtocell & \(20\ \mathrm{dBm}\) (masi) \(0\ \mathrm{dBm}\) (mini) \\ Macrocell radius & \(500\ \mathrm{m}\) \\ Femtocell radius & \(10\ \mathrm{m}\) \\ Thermal Noise Density. & \(-174\ \mathrm{dBm}/\mathrm{Hz}\) \\ Penetration Loss. & \(20\ \mathrm{dB}\) \\ Lognormal shadowing the standard deviation (macrocell) & \(10\ \mathrm{dB}\) \\ Lognormal shadowing the standard deviation (femtocell) & \(4\ \mathrm{dB}\) \\ Noise figure in user & \(9\ \mathrm{dB}\) \\ Minimum separation from Users Equipment(UE) to HeNB & \(20\ \mathrm{cm}\) \\ \hline \hline \end{tabular}
\end{table}
Table 1: Simulation parameters.  
To summarize, the proposed ANS power control technique effectively and efficiently balances the throughput performance by reducing the interference to the MUE in the vicinity of the HeNB and optimizes the femtocell coverage and capacity. In Table 2, a comparison of average throughput for macro users and femto users is shown, under the existing and proposed power technique.  
Moreover, the ANS technique is a reactive power control technique, as it reacts only when the interference indication function indicates that the interference level is higher than the threshold level in the MUE and receives a message from the macrocell, whereas other above-listed techniques are proactive. In the proactive power control technique, the femtocell depends on the measured value of the  
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RSRP (Reference Signal Received Power) to set its downlink transmission power, irrespective of the presence of a victim macro user in its coverage area. Thus, the reactive power control technique can competently deter the irrelevant tuning of transmission power.