# Experiencing LoRa Network Establishment on a Smart Energy Campus Testbed
## 5 Experiments for LoRa MAC  
This section examines LoRa MAC performance in the combined indoor and outdoor environment. To answer the question, \"how do application parameters and regional, regulative parameters influence LoRa performance?\", we set up a simulation by taking the results from the previous section, running experiments, and analyzing the results. The goal of this section is to enumerate the impacts of the parameters and to find the optimal set of parameters for the smart energy campus scenario. Preliminary  
In the simulation, a gateway was at the center of a 2690 \(\times\) 2690 m area, and nodes were deployed according to a uniformly random distribution around the gateway. Figure 13 shows the deployment of 3000 nodes, and all of them are within 1344.6 m from the gateway. By adopting the recommended node deployment strategy from [21], the distance from the gateway to a node determines the SF value at the node. To this end, we take the values from Table 5 in Section 4 (see the case of 90% communication reliability). Nodes whose distance is less than or equal to 630.9 m had SF values set to 7, nodes with a distance between 630.9 m and 751.3 m had SF 8, and so on. In this way, 1380 nodes are set to SF 7 (46%), and 330 nodes are set to SF 12 (11%). We note that this deployment strategy aims to maximize  
Figure 12: To estimate the maximum communication ranges more accurately, this section analyzes communication reliability at the maximum distance. The maximum range decreases to 1.34 km to achieve 90% reliability. \begin{table}
\begin{tabular}{l|c c|c c|c c} \hline  & \multicolumn{2}{c|}{**50\%**} & \multicolumn{2}{c|}{**70\%**} & \multicolumn{2}{c}{**90\%**} \\ \cline{2-7}  & **RSSI** & **Coverage** & **RSSI** & **Coverage** & **RSSI** & **Coverage** \\  & **[dBm]** & **[m]** & **[dBm]** & **[m]** & **[dBm]** & **[m]** \\ \hline SF 7 & \(-124\) & 953.5 & \(-121.1\) & 804.7 & 116.9 & 630.9 \\ SF 8 & \(-127\) & 1135.4 & \(  
the network coverage, but it is possible that the collision rate increases as a result of the excessive number of nodes set to SF 7. A node (e.g., \(N_{1}\)) periodically transmits a data packet at an EIRP of 14 dBm (i.e., 11 dBm of transmission power and 3 dBi of antenna gain). When \(N_{1}\) transmits a packet, all other nodes and the gateway calculate the received signal power using the path loss, the Gaussian random noise obtained in the previous section, and the distance from the transmitting node. They then determine whether the data signal reaches them, implying that they can sense whether a channel (e.g., \(C_{1}\)) is in use. If \(C_{1}\) is available, another node (e.g., \(N_{2}\)) can start transmitting its own data. If not, \(N_{2}\) randomly selects another channel (e.g., \(C_{2}\)) out of 7 different channels, jumps to \(C_{2}\), and ensures that \(C_{2}\) is not in use before sending data out. We note that the simulation implements 7 different channels according to the LoRa specification, ranging from 922.1 MHz to 923.3 MHz, with 14 dBm of EIRP in Korea [12]. If \(C_{2}\) is unavailable, \(N_{2}\) hops to another channel (\(C_{3}\)). With this hopping technique, nodes try to avoid collisions. Upon receiving a data packet, the gateway decodes data only if the received power is greater than the receiving sensitivity (also known as the decoding threshold). Otherwise, it processes the packet as a loss. Also, all packets received at the gateway simultaneously are discarded because they are considered to be collisions. To focus on data delivery performance only, the nodes in the experiments transmit data messages of the unconfirmed type, indicating that the gateway does not send an acknowledgment back to the sender upon receiving a data packet.