# IRS-Enabled Ultra-Low-Power Wireless Sensor Networks: Scheduling and Transmission Schemes
## 6 Results  
The simulation parameters are provided in Table 3. We consider a BS located at \((0,0)\) m, \(L\) LNs deployed on an arc of radius \(r\) randomly chosen between \(10\) m \(<r<20\) m and a sector angle \(\theta_{sec}\) between \(-\pi/6<\theta_{sec}<\pi/6\) with respect to the BS, and a single antenna user located at \((25,0)\) m. Thus, the ISNs are distributed within a difference of sector areas such that \(A=\frac{(20^{2}-10^{2})\pi}{6}\) m\({}^{2}\) and the simulated network area \(A_{network}\), including the BS, user, and ISNs, is \(A_{network}=\frac{20\pi}{3}\times 25\) m\({}^{2}\approx 524\) m\({}^{2}\). Path loss factors are computed at 2.5 GHz for the 3 GPP Urban Micro (UMi) scenario from TR36.814 (cf. [21] Section V). Generally, the coverage area of the IRS-equipped WSN depends on the constrained transmitting power of the BS, wavelength of the carrier \(\lambda_{c}\), and number of IRS-equipped sensors. In this layout, the number of elements of the IRS is \(N\) and the size and spacing of the elements depends on \(\lambda_{c}\). Hence, the size of the IRS is in the order \(\lambda_{c}^{2}N\). If we assume a carrier frequency of 30 GHz which is equivalent to \(\lambda_{c}=1\) cm and \(N=32\), then the area of each IRS is approximately \(A_{IRS}=32\) cm\({}^{2}\). In Figure 5, we plot the rate of the scheduled sensor under different scheduling protocols. First, the benchmark is defined as scheduling the ISN with the largest SNR under an an optimal phase configuration at the IRS while having perfect CSI. This is not achievable in practice in this system unless there are control links between the IRS and BS. \begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Value** \\ \hline
**Array Parameters** & \\ \hline BS configuration & Uniform linear array \\ IRS configuration & Uniform planar array \\ Antenna gain & 5 dBi \\ \(d_{BS}\), \(d_{RS}\) & 0.5\(\lambda_{c}\) \\ Noise level & \(-30\) dBm \\ \hline
**Path Loss** & \\ \hline Model & \(\frac{10^{-C/10}}{d^{2}}\) \\ \(C\) (Fixed loss at \(d=1\) m) & 25 dB (\(\beta_{1}^{2}\)), 30 dB (\(\beta_{2}^{2}\)) \\ \(\alpha\) (Path loss exponent) & 2.2 (\(\beta_{1}^{2}\)), 3 (\(\beta_{2}^{2}\)) \\ \hline
**System Dimensions** & \\ \hline \((L,N,M)\) & \((32,32,64)\) \\ Time slots \(t\) & 2000 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Simulation parameters. Assuming that the time for feedback from the user to the BS is negligible, it is apparent that OS performs best, followed by PF, then RR. Note that for a larger number of elements \(N\) at the IRS there is an increase in performance thanks to the resulting increase in channel gain. The significance of using an optimal configuration of IRS \(\mathbf{\Theta}_{l}^{*}\) in each scheduled ISN versus a random configuration \(\mathbf{\Theta}_{l}^{rand}\) is showcased in Figure 6, where it can be seen that if there is a control link between the BS and ISNs and an optimal phase configuration is deployed for the cascaded channel, we obtain better performance. Note that OS performs better in terms of outage than RR and PF with both the random phase and optimal phase configurations. The reason for this is that OS targets enhanced performance, which is equivalent to minimizing the system outage probability. Because OS searches for the ISN least likely to be in outage and schedules it, system outages are less likely overall than in other schemes, such as RR and PF, which target fairness between ISNs instead of overall performance. This highlights the significance of the OS protocol. Next, we focus on the fairness metric in the proposed scheduling schemes. For instance, OS chooses the ISN with the best channel quality during each frame. This approach can be  
Figure 5: Rate vs. transmitting power \(P\) for different scheduling protocols. Figure 6: System outage probability vs. average SNR for all ISNs. The system outage probabilities for the OS, PF, and RR scheduling schemes are calculated according to Equations (36), (40), and (42), respectively. greedy, as weak ISNs may never be scheduled.