# Smart Preliminary Channel Access to Support Real-Time Traffic in Wi-Fi Networks
## 5 Results
### Dependences of the Efficiency on the Delay Quantile  
Let us compare the methods depending on the delay requirements. To do it, we consider how the efficiency of the studied methods depends on the delay quantile. Figures 6 and 7 show the results of six experiments for different values of RTA STAs number, RTA traffic period, and \(\sigma\). To satisfy the requirement for the delay quantile (abscissa axis), it is necessary to set some TXOP Limit value, which in turn affects the efficiency of non-RTA STAs (ordinate axis). Thus, the plots in Figures 6 and 7, including the horizontal parts, show the maximum efficiency that each method provides for a given delay quantile limit. First, we consider the strict requirements for the delay (3-5\(\,\mathrm{ms}\)). Figure 6a shows the simulation results for \(T_{period}=20\,\mathrm{ms}\), \(\sigma=10\,\mathrm{\SIUnitSymbolMicro s}\), and \(M=5\). The maximum efficiency of the PCA and the Smart PCA is 48%. At the same time, Tuned EDCA can provide a delay less than 5\(\,\mathrm{ms}\) with the same efficiency. Thus, the area where the Smart PCA gains in efficiency for \(T_{period}=20\,\mathrm{ms}\) is negligible. It happens because such traffic periods and high \(M\) values result in high intensity of traffic; thus, there is high contention between RTA STAs during the reservations. The results for \(T_{period}=50\,\mathrm{ms}\) with the same values of \(\sigma=10\,\mathrm{\SIUnitSymbolMicro s}\) and \(M=5\) are shown in Figure 6b. In this case, the size of the area where Smart PCA provides the given quantile with the best efficiency becomes significant due to lower intensity and hence less frequent contention between RTA STAs. So, if the delay requirement lies between  
Figure 5: Delay quantile and efficiency vs. TXOP Limit in case of \(T_{period}=20\,\mathrm{ms}\), \(\sigma=10\,\mathrm{\SIUnitSymbolMicro s}\), \(M=5\). 3.2 ms and 4.6 ms, the efficiency gain reaches 100% compared to the Tuned EDCA and 30% compared to PCA. For stricter requirements, the efficiency for PCA and Smart PCA are equal because the TXOP Limit value is set low and condition (1) is met, so the methods have the same PCA procedure. Let us increase the period to \(T_{period}=100\) ms (Figure 6c). The area of delay requirements for which the Smart PCA is most effective becomes wider for the same reason as above. Efficiency gain compared to Tuned EDCA reaches 100% (\(\approx\)70% against \(\approx\)36% for 3 ms delay limit) and 40% compared to PCA (\(\approx\)78% against \(\approx\)56% for 3.2 ms delay limit). As the period of RTA traffic increases, the efficiency advantage of the Smart PCA grows, because RTA transmissions consume channel time less often. Figure 6d shows the results for the same period \(T_{period}=100\) ms and the RTA STAs number \(M=5\), but for increased \(\sigma=100\) ms. The Smart PCA guarantees a delay of 4 ms with maximum efficiency of 76%, while the Tuned EDCA provides the same delay with an efficiency of 68%. Thus, with a large value of \(\sigma\), the efficiency gain of the Smart PCA drops from about 100% to 10%. The reason is that an increase in \(\sigma\) lengthens the interval \(T_{exp}\), due to which the PCA procedure consumes more channel time. Let us reduce the number of RTA STAs to \(M=3\) for \(T_{period}=20\) ms and \(\sigma=10\) us (Figure 7a). Compared to the scenario with \(M=5\), the area where the Smart PCA shows the best efficiency increases. At the same time, the gain in efficiency compared to the Tuned EDCA reaches values of more than 100%, and compared to the PCA, it reaches more than 30%. Thus, in scenarios with a small number of RTA STAs, the developed method is the most efficient under strict delay requirements for RTA traffic with a period of \(T_{period}=20\) ms. It is explained by the fact that a decrease in the number of RTA STAsreduces the total consumption of the channel time and the delay associated with contention between RTA STAs.