# Power Optimization in Multi-Tier Heterogeneous Networks Using Genetic Algorithm
## 9 Results and Discussion
### Power Consumption Performance  
As 5G networks require much less energy to transmit the same data as 4G, they are more efficient in the ratio of power consumption to traffic. However, 5G's higher speed and bandwidth might also increase the number of devices using the network extensively; this could become a problem. In particular, IoT devices equipped with multiple sensors can present a challenge due to their constant transmission of large amounts of data, as they are not connected to the electrical grid. On the other hand, a sensor that transmits data seldom can do this sporadically in a 5G network, while in 4G environments, it has to be constantly transmitting. Likewise, while 5G's power consumption will require more access points per square kilometer, these will only need as much power as required--whereas predecessor networks were always \"on\". In this section, the power consumption of a network is analyzed based on the number of users and the signal-to-interference ratio threshold \((SIR_{T})\) using various power optimization techniques in the proposed model. Power optimization refers to finding the best weights for transmitting access points to each user, increasing the spectral efficiency. Three different optimization techniques, (i) particle swarm optimization, (ii) the genetic algorithm, and (iii) the modified genetic algorithm, were used to optimize the weights with which the access point transmits to each user. Each user selects the access point according to the proposed user-scheduling algorithm, and then, the access point assigns an optimal power for downlink transmission, then this power is calculated, which is shown in Figure 10. The graph shows that the downlink power consumption for each access point increases with the increase in the number of users attached to a given access point. SIC-based hybrid transmit precoding is used to cancel out interference in multi-tier heterogeneous networks. However, transmitting data from an AP to one user can interfere with neighboring users. This interference can be mitigated by using an SIC-based receiver, but it still contributes to the overall energy consumption during the data capture and communication processes. The energy consumption from transmission and reception is modeled as  
\[E_{rx}(b)=E_{elec}b \tag{26}\]  
\[E_{tx}(d,b)=E_{elec}b+E_{amp}bd^{n} \tag{27}\]  
where \(E_{elec}\) represents the electronic transmission energy, \(E_{amp}\) represents the amplification energy, \(d\) represents the distance between the transmitter and receiver, \(b\) represents the number of bits, and \(n\) represents the path loss exponent. The power consumption of each user for a given period of time \(t\) is now calculated as  
\[P_{tot}=\frac{E_{tot}}{t}=\frac{E_{rx}(b)+E_{tx}(d,b)}{t} \tag{28}\]  
As the number of nodes increases, the users' power consumption also increases. This is because there is more interference and more transmission is required to achieve the desired signal-to-interference ratio threshold. Power consumption is lower for the modified genetic algorithm as it optimizes the weights and transmission power. It shows that the power consumption for equal power allocation is the highest as it allocates equal power to all the users irrespective of the distance and channel gain. In Figure 11, the SIR threshold is gradually increased from \(-5\) dB to \(20\) dB, and then, the power consumption is evaluated for the fixed number of users. The number of users was fixed to be \(50\). The result showed that the power consumption from \(-5\) dB to \(5\) dB remained almost constant using all of three optimization techniques because the given SIR threshold can be achieved with less power; hence, the power consumption was lower at a lesser SIR threshold. As the SIR threshold increased, power consumption also increased. For an SIR threshold greater than \(5\) dB, the power consumption increased exponentially because more power was required for transmission to achieve the given threshold and maintainthe quality of service.