# SINR-Based MCS Level Adaptation in CSMA/CA Wireless Networks to Embrace IoT Devices
## 5 Performance Evaluation
### The Same Number of Access Points and Users  
In this section, we first show the simulation results when both the number of APs and the number of wireless devices increase from 2 to 60 (i.e., 2, 4, 6, 10, 20, 30, 40, and 60) in a circular area with a radius of 1000 m. In Figure 9, we show the total (i.e., aggregated) throughputs achieved by all wireless devices when a fixed MCS level is used for communications of all participants in different PPP densities of APs for 2 s. The total throughputs are averaged values from 10 repetitions of each scenario. From the simulation results in Figure 9, we can see a trend of higher total achieved throughputs with higher MCS levels and higher densities of APs (and wireless devices). In Figure 9, we also show total throughputs achieved by all wireless devices when all APs use the proposed automatic MCS level adaption algorithm. The simulation results in Figure 9 show that APs using the proposed algorithm utilize the resources of the simulated IEEE 802.11a wireless networks almost as effectively as the highest MCS level in Table 1 (i.e., 3), although the APs do not always use the highest MCS level. In Figure 10, we show the ratios (in percent) of the number of discarded packets by retry limit events to the number of packets sent by APs during 2 s of simulation time. In CSMA/CA wireless networks, if a sender does not receive an ACK frame corresponding to the transmitted packet in a given time, which is decided by the short interframe space (SIFS) [8] and the transmission speeds of MCS levels, it is counted as a timeout. The sender retransmits the timeouted packet until the number of consecutive retransmissions for the packet reaches a limit called the retry limit. When the number  
Figure 9: Total achieved throughputs. of retransmissions for a packet reaches the retry limit (i.e., a retry limit event occurs), the packet is discarded by the sender. The simulation results in Figure 10 show a trend of higher retry limit ratios with higher MCS levels. In Figure 10, we also show the simulation results of the retry limit ratios when all APs use the proposed automatic MCS level adaption algorithm. From the results in the figure, we can see that the proposed algorithm keeps the retry limit ratios comparable to those of the lowest MCS level (i.e., 0) for most AP densities. The simulation results in Figures 9 and 10 clearly show that the proposed algorithm effectively and efficiently utilizes network resources by adapting the MCS levels according to the environments of the IEEE 802.11a wireless networks. In Figure 11, we show the average values of the time-averaged MCS levels used by all APs for their associated wireless devices during 2 s of simulation time with 95% confidence intervals. The simulation results show that the APs using the proposed algorithm increase their MCS levels when the densities of APs and wireless devices increase. This result implies that the overall SINRs of the wireless networks are increasing as the PPP density of APs increases. This is because the received signal strengths increase as the distances between wireless devices and their serving APs decrease while the CSMA/CA mechanism controls interference among participating nodes. In addition, in Figure 12, we show cumulative distributions of user throughputs with different MCS levels when both the number of APs and the number of wireless devices are 60. The simulation results in the figure show that there is higher dispersion of throughputs when higher MCS levels are  
Figure 11: Average MCS levels with 95% confidence intervals. Figure 10: Ratios of retry limits to sent packets. used for communication. In the figure, the cumulative distributions of user throughputs with the proposed algorithm show less dispersion than that of the highest MCS level (i.e., 3). In Figure 13, we show the fairness among users using the achieved throughput by each user with different MCS levels for different AP densities.