# Energy and Spectral Efficiency Balancing Algorithm for Energy Saving in LTE Downlinks
## 4 Performance Evaluation of the Proposed SET algorithm
### Simulation Setup  
The simulation scenario in this section is based on two types of networks served by a single eNodeB; (1) A non-congested network with a number of UE less than 100, where the network density is under normal non-congested condition [22]. (2) A congested network with a number of UE greater than 100 [30]. The total energy consumed by the entire network is the summation of energy dissipated during the transmission and receiving processes, which comprises energy spent in the control and data messages in both modes.  
A cellular network that comprises homogeneous macro-cells with a hexagonal tessellation is presented as in Figure 4. The eNodeB is placed at the center of each cell, and UE is assumed to be served by the nearby eNodeB. Spectrum resources and power are assumed to be allocated equally to all cells in the network. Two distinct eNodeB antenna configurations are used in this section: (1) omni-directional and (2) directional antennas. An omni-directional antenna transmits radio links in all directions but has limited network capacity because of the high interference.  
Figure 3: The adopted energy consumption model.  
To alleviate interference caused by an omni-directional antenna, cell sectoring, which divides cells into sectors (as 120\({}^{\circ}\) or 60\({}^{\circ}\)) using a directional antenna, is proposed. The transmission and receipt of radio signals in a certain direction result in low interference, high spatial reuse, long transmission range and improved network capacity. The cell sectoring by antenna patterns has been shown in Figure 5.  
To evaluate the performance of any cellular network, an important metric that should be considered is the signal-to-interference-plus-noise ratio (SINR). Thus, the SINR of user's cells in a region served by cell \(k\) is calculated using Equation (9) based on Reference [31]:  
\[SINR=\left(\frac{P_{k}\times C_{k,n}}{\sum\limits_{i=1,\text{ except }i=k}^{I}P_{i}\times C_{i,n}+P_{n}}\right) \tag{9}\]  
where \(P_{k}\) denotes the transmission power of the serving cell \(k\), \(C_{k,n}\) represent the channel gain from the serving cell \(k\) to \(n\) number of UE, \(I\) is the set of all interfering cells in the region. Moreover, \(P_{i}\) is the transmission power of each \(i\)th neighboring cell, \(C_{i,n}\) represents the channel gain from the \(i\)th cell to \(n\) number of UE, \(P_{n}\) is the white Gaussian noise power, where the channel gain in this research considers both transmission and receiving antenna gains along with their path loss gain.  
The energy saving algorithm consists of one eNodeB and the UEs that are uniformly distributed around the eNodeB as presented in Figure 6. All the simulation experiments setup have been adopted from LTE Release 8 [32]. These experiments have been conducted using the Vienna system-level simulator [33], in which the Multi-Input Multi-Output (MIMO) antennas and a system bandwidth of 5 MHz have been used. The simulation time in all experiments is 100 s, which is more than enough to show all stages of the system. As for updating the transmission power, it has been done at the beginning of each transmission time interval (TTI), where each second has 1000 TTIs, while the thermal noise density is set to \(-174\) dBm/Hz during all simulation experiments.  
The network topology used in this work has been adopted from [16], which is used to evaluate the energy saving algorithm. As shown in Figure 7, the topology consists of one eNodeB with several Mobile Users (MUs) that are uniformly distributed in a congested network including MU\({}_{1}\), MU\({}_{2}\),..., MU\({}_{N}\), where \(N>100\). Table 1 shows the experimental setup of the simulation parameters.  
Figure 4: Omni-antenna in cellular network with interference.  
Figure 5: Antenna patterns.