# Resource Allocation to Massive Internet of Things in LoRaWANs
## 5 Experimental Results and Analysis
### Proposed Channel-Adaptive SF Scheme in a Confirmed Mode  
The proposed scheme was evaluated under a _LOG_ path loss and an urban environment, as shown in Figure 5a,b, respectively. As shown in Figure 5b, a square-shaped building based on the Manhattan layout model and correlated shadowing model was adapted in this work [51]. If an ED is randomly deployed inside this building, the transmission from this ED will suffer from high penetration losses. The building parameters utilized in an urban environment are presented in our previous work [52]. When the channel has fading, shadowing, and attenuation caused by the urban environment, it is more difficult for the EDs to gain connectivity with a GW, thereby resulting in many EDs going out of range [53]. For this reason, the GW radius is limited to 3410 m. During the simulation experiment, ED transmits a single packet in UL every 1 h, including a random time distributed between 0 and 1000 s to avoid simultaneous packet transmission [54].  
Figure 6 presents the performance analysis of the typical and proposed channel-adaptive SF schemes. As shown in Figure 6a,b, the \(SR\) generally decreases with a massive number of EDs joining the network in both schemes. Therefore, when an ED does not receive an ACK, it transmits at low data rates after a few retransmissions. Owing to the higher ToA, the collision probability increases. When a packet collision happens, the two EDs involved in the collision schedule a retransmission time imposed by the duty cycle restriction. The higher the number of retransmissions, the more packets  
Figure 4: Collision overlap time of intra- and inter-SF interference using \(SF_{(i,j)}\).  
Figure 5: ED distribution under the condition of GW radius = 3410 m: (**a**) _LOG_ path loss only; (**b**) _LOG_, shadowing, and building penetration losses.  
are lost because of interference [2]. That is, in a massive LoRaWAN network, a higher traffic load increases the chances of collision probability, and most of the RW is missed due to the duty cycle limitations [8; 37]. As a result, more EDs with the SF management scheme transmit with high SFs and cause more congestion, and the network loses the advantage of orthogonality between different SFs. However, the proposed channel-adaptive SF scheme increases the data rate when ACK failures are reduced, thus lowering the SF and yielding a better \(SR\) of up to 7.5% and 7.8% for Figure 6a,b, respectively. Furthermore, the performance of both the SF approaches is lower in Figure 6b than in Figure 6a. This is due to the signal strength being significantly decreased by the building penetration losses, which results in a lower \(SR\). In the case of an urban environment, many of the EDs cannot reach the GW due to the unfavorable channel that leads to a high packet loss. As these EDs stay active and cause interference to the nearby EDs, the scalability of the LoRaWAN is retained. Another possibility is that the duty cycle limitations imposed by the LoRaWAN do not allow such transmissions if the EDs reach the maximum allowed time. Therefore, the \(\hat{\mu}D\) and \(\hat{\mu}D_{ack}\) delays go up in both the cases as shown in Figure 6c,d, and Figure 6e,f, respectively.