## Appendix A Simulation Setup for the IEEE 802.11 Family
### Channel Conditions for IEEE 802.11 Protocols  
The channel medium between the transmitter and receiver in IEEE 802.11 protocols is affected by multiple channel propagation models and SNR levels. A set of channel models was designed and studied thoroughly to provide sufficient channel models for IEEE 802.11 PHY layer simulation and performance testing for IEEE 802.11n WLAN [79], 802.11 ac [80], 802.11 ax [81], and 802.11a [82]. Each channel model is designed for a certain environment. Each channel has a certain number of clusters, where each cluster includes a set of taps. The number of clusters, number of taps, the value of Root mean square (RMS) delay (\(\sigma_{RMS}\)), the maximum delay (\(\sigma_{Max}\)), and the standard deviation \(\sigma\) value of shadow fading are all characterized in each model in case of Line-of-Sight (LOS) and NLOS conditions. Moreover, there are two key signal propagation models for WLAN channel modeling: (1) Large-scale propagation (or large-scale path loss) and (2) small-scale fading. For large scale path loss, the considered path loss model \(L(d)\) for indoor WLAN channel is based on the following equation:  
\[L(d)= \begin{cases}L_{FS}(d)&\text{if }d\leq d_{BP}\\ L_{FS}(d_{BP})+3.5 log10(d/d_{BP})&\text{if }d>d_{BP}\end{cases}  \tag{1}\]  
where \(d\) is the distance between the transmitter and receiver, \(L_{FS}\) is the free space loss (log-distance model) for the slope of 2 for up to break-point distance \(d_{BP}\) and 3.5 after \(d_{BP}\). The \(d_{BP}\) for our channel model is 5 m. Generally, the breakpoint distance is assumed to be the boundary for LOS and NLOS conditions [79]:  
\[L_{FS}(d)=-10 log_{10}\bigg{(}\frac{G_{t}G_{r}\lambda^{2}}{(4\pi d)^{2}}\bigg{)} \tag{2}\]  
where \(G_{t}\) and \(G_{r}\) are the transmitter and the receiver gain, which we assume equal to 1, \(\lambda\) is the wavelength of the transmitted carrier frequency \(f_{c}\) at speed of radio frequency (RF) \begin{table}
\begin{tabular}{c c c c c} \hline
**Parameters** & **IEEE 802.11a** & **IEEE 802.11n** & **IEEE 802.11 ax (_Wi-Fi6_)** & **IEEE 802.11 ac (_Wi-Fi5_)** \\ \hline Modulation & OFDM & HT-OFDM & HE-OFDM & VHT-OFDM \\ Channel bandwidth & 20 MHz & 20 MHz & 20 MHz & 80 MHz \\ Preamble & Long & Long & Long & Long \\ PSDULength & 1000 & 1000 & 100 & 1035 \\ Number of transmitted antennas & 1 & 1 & 1 & 1 \\ Modulation and coding scheme & 0 “BPSK (Binary & 0 ”BPSK” & 0 ”BPSK” & 0 ”BPSK” \\ Spatial Mapping Matrix & N/A & 1 & 1 & 1 \\ Spatial Mapping & N/A & Direct & Direct & Direct \\ Channel Coding & N/A & BCC (Binary & LDPC (Low-density & BCC \\  & convolutional coding) & parity-check coding) & BCC \\ Number Space Time Streams & N/A & 1 & 1 & 1 \\ \hline \end{tabular}
\end{table} 
Table 1: WLAN standards simulation parameters. signal \(\lambda=\frac{\
u}{f_{c}}\). For our implementation, the RF signal speed \(\
u\) (approximately the speed of light) is equal to \(\
u=c=3\times 10^{8}\) m/sec. \[L_{FS}(d)=10 log_{10}\bigg{(}\frac{(4\pi d)^{2}}{\lambda^{2}}\bigg{)} \tag{10}\]  
\[L_{FS}(d)=4\pi dB+2.10 log_{10}(d) \tag{11}\]  
In our simulations, we consider the channel path loss model in an indoor and open environment. Thus, _Model B_ delay profile is selected as a channel model for IEEE 802.11 ac, 802.11 ax, and 802.11n. _Model B_ represents a typical sizable open space and office environments with NLOS conditions and 100 ns RMS delay spread for IEEE 802.11. The parameters used to model path loss to provide sufficient channel models for IEEE 802.11n PHY layer simulation are detailed in [79], for IEEE 802.11 ac PHY layer in [80], and for IEEE 802.11 ax PHY layer in [83]. The channel path loss model for IEEE 802.11a is simulated as a Rayleigh channel model, with a sample rate of \(f_{s}=20\) MHz, and the carrier frequency \(f_{c}\) is 5.25 GHz. The shadow fading (also known as log-normal shadowing) is also considered in our analysis. It is modeled with a zero-mean Gaussian random variable \(x\) and a standard deviation \(\sigma\), and added to the path loss model as given by  
\[L(d)=