# Resource Allocation to Massive Internet of Things in LoRaWANs
## 5 Experimental Results and Analysis
### ED Sensitivity-Based SF Allocation in a Confirmed Mode  
In Figure 7, the number of EDs is kept fixed at 1000, while varying the distance in an urban environment. Figure 7a shows a declining trend in \(SR\), as the distance is increased. The decreasing trend of the \(SR\) is because of the high interference among the SFs or the unreachability of the GW [55]. In the case of the proposed ED sensitivity method, the distribution of SFs is very uniform, as shown in Figure 7b, resulting in an enhanced \(SR\) of up to 5% on an average as compared to GW sensitivity method. However, the performance of the ED sensitivity decreases gradually when the signal strength of an ED increases or decreases, as the distance is reduced or increased from the GW, respectively. This is because of the assignment of the SFs based on the sensitivities of the EDs, wherein the UL packets are successful, but the ACKs are lost. Therefore, EDs retransmit packets, causing significant congestion in the network and resulting in packet loss.  
Figure 6: Performance of the SF assignment schemes under the various conditions of channel and traffic loads: (**a**) \(SR\) under only the path loss; (**b**) \(SR\) under the path loss, shadowing, and other RF features; (**c**) end-to-end delay under only the path loss; (**d**) end-to-end delay under the path loss, shadowing, and other RF features; (**e**) ACK delay under only the path loss; (**f**) ACK delay under path loss, shadowing, and other RF features.  
On the other hand, in Figure 7a, the GW sensitivity SF assignment scheme (uses sub-optimal fixed-width SF rings) shows a decreasing tendency in \(SR\) with increasing distance. More than 50% of the end devices use SF 7, as shown in Figure 7c, thus leading to substantial packet loss owing to the interference and retransmission. The probability-based SF method is primarily based on a theoretic distribution of data rates, as presented in [33]. The corresponding SF assignment ratio of the probability-based SF allocation method is shown in Figure 7d. The EDs are forced to use a given SF, resulting in a significant impact on the \(SR\). Additionally, we found a similar observation regarding [33], as presented in [2]. Lastly, a random SF allocation algorithm performs worse than ED and the GW sensitivities methods in terms of \(SR\) because of the unfair distribution of SF to the EDs. Therefore, it is a sub-optimal choice for the SF assignment [56].  
Figure 8a,b present the \(\hat{\mu}D\) and \(\hat{\mu}D_{ack}\) delays in the confirmed mode with a maximum of eight transmissions. In general, \(\hat{\mu}D\) and \(\hat{\mu}D_{ack}\) delays increase by increasing the distance, as the \(SR\) declines, and more retransmissions are needed to deliver a packet successfully. \(\hat{\mu}D\) and \(\hat{\mu}D_{ack}\) delays are maximum at GW radius = 5000 m, which is because of the number of interfered packets increases, resulting in retransmissions. \(\hat{\mu}D_{ack}\) correspondingly considers the time for the ACK reception; hence, the results show a higher \(\hat{\mu}D_{ack}\) as compared to \(\hat{\mu}D\).