Pronóstico de estos pacientes:

The power consumption of backhaul in macrocell RAN is often omitted because its value is relatively small compared to the power consumption of a macro base station. However, this is not true for the small cells or HetNets. The impact of the backhaul power consumption on the RAN ECG is evaluated by rewriting the ECG expressions to include the backhaul power consumption in the different deployments, as shown in (3.33).

𝐸𝐶𝐺 = 𝜆𝑚,𝑟𝑒𝑓.(𝑃𝑚+𝑃𝑏ℎ,𝑚) 𝜆𝑚.(𝑃𝑚+𝑃𝑏ℎ,𝑚)+𝜆𝑠.(𝑃𝑠+𝑃𝑏ℎ,𝑠) ,

( 3.33)

Where 𝜆𝑚,𝑟𝑒𝑓 refers to the macro cell density in the reference deployment, 𝜆𝑚 is the density of macro cells in the deployment being tested, which is equal to zero in pure small cell only deployments, 𝑃_𝑏ℎ,𝑚 refers to the backhaul power consumption of the macro base station. A fibre optic is always assumed for the macro cell backhaul in this analysis. A value of 10 watts

0 20 40 60 80 100 120 140 160 180 200 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 TPG ECG

Macro cell RAN Macro-Micro Het Net Macro-Pico Het Net Micro cell RAN Pico cell RAN

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is often proposed in the literature for fibre backhaul power consumption per macro site [126]. 𝑃_𝑏ℎ,𝑠 refers to the backhaul power consumption in small cells. 𝑃_𝑚 ad 𝑃_𝑠 denote the power consumption of macro and small cells, respectively.

Accurately modelling the backhaul power consumption requires a knowledge of the exact topology of the network and knowing the power consumption of the transmission links and aggregation nodes associated with the backhaul. Three values of backhaul power consumption are considered to model both fibre and wireless backhaul links [131].Microwave backhaul links are an attractive option in terms of cost and installation time, but due to their high power consumption, they are unlikely to be used in small cell scenarios. The ECG is calculated for each deployment type by (3.33) at three assumed values of backhaul power consumption (10, 20& 40 watts). As fibre backhaul links are always assumed to be used in the case of macrocell RANs, the backhaul power consumption of macrocells is set to equal 10 watts while the backhaul power consumption for small cells and HetNet varied from 10 to 40 watts. Figure 3- 30 illustrates how the ECG of micro and picocell only RANs degrades as the backhaul power consumption increases. For example, the ECG of a picocell only RAN degrades from 0.2 to around 0.1 at a TPG of 100 when the backhaul power consumption increases from 10 watts to 40 watts, which is equivalent to a 2 times increase in the RAN power consumption. The same trend is observed in the case of microcell RANs. When comparing the three deployment types, the results show that even if 40 watts of backhaul power consumption is assumed, the pico cell RANs still consumes the least energy for TPG values above 70 while the microcell RANs consumes the least amount of energy for TPG values from 4 to 70.

The impact of the backhaul power consumption on the ECG of HetNet is shown in Figure 3-31. The results show that although the backhaul power consumption significantly degrades the ECG of both macro/pico and macro/micro HetNets, they are still more energy efficient than the macro cell RAN. The macro/pico HetNet is the most energy efficient RAN for all the TPG values above 1.8.

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Figure 3-30: The backhaul power consumption impact on the ECG of macro and small cells deployments

Figure 3-31: The backhaul power consumption impact on the ECG of HetNet RANs

100 101 102 0 0.2 0.4 0.6 0.8 1 1.2 1.4 TPG ECG Macro Only P_bh,m=10 W Micro Only P_bh,s=10 W Micro Only P_bh,s=20 W Micro Only P_bh,s=40 W Pico Only P_bh,s=10 W Pico Only P_bh,_s=20 W Pico Only P_bh,s=40 W 1 10 50 0 0.2 0.4 0.6 0.8 1 1.2 TPG ECG Macro Only P_bh,m=10 W Macro-Micro P_bh,s=10 W Macro-Micro P_bh,s=20 W Macro-Micro P_bh,s=40 W Macro-Pico P_bh,s=10 W Macro-Pico P_bh,s=20 W Macro-Pico P_bh,s=40 W

87 3.10 Summary

This chapter has highlighted the motivation for proposing a different evaluation framework for the energy efficiency in cellular networks. The process of modelling the power consumption in LTE base stations has been detailed, followed by presenting the throughput and energy efficiency metrics and how they can give more insights into the energy consumption than the widely-used bit/J. The system model used in this chapter and through this thesis is also explained. To demonstrate how this framework can be used, it was applied to various case studies, including macro only, small cells, and heterogeneous deployments. For each deployment type, the TPG and ECG are calculated to avoid any misleading conclusion about the RAN energy consumption when using only the bit/J as a metric. Interestingly, the results showed that pico cell only deployments can attain up to 3 times increase in the TPG and 2.27 times increase in the ECG simultaneously when compared with macro only RANs at high target capacities. While it offers 2 times more capacity and reduces the energy consumption by 12% when compared with the macro/pico HetNet deployments. Finally, in addition to comparing the ECGs of different RAN types, the impact of backhaul power consumption on the overall RAN ECG is investigated for three backhaul power consumption levels. The results have shown that both small cell and HetNets deployments are very sensitive to the level of backhaul power consumption, but they never lose their superiority over the macro cell RAN in terms of the energy consumption when the same target throughput is required.

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Chapter 4