# RIS-Assisted Network Slicing Resource Optimization Algorithm for Coexistence of eMBB and URLLC
## 5 Simulation Results and Analysis
### Performance Evaluation of URLLC Allocation Policies  
In this paper, the heuristic URLLC allocation algorithm based on RIS pre-configuration is simulated and compared with the following two types of schemes.  
* Proportional Fair (PF) scheduling algorithm: The basic idea of this algorithm is to consider the ratio of instantaneous rate and long-term average rate when selecting users and to adjust different users by using the weight value. The final goal is to consider both system performance and user experience.
* Iterative algorithm for joint resource allocation (the algorithm proposed in the literature [4]): the transmission power of URLLC users is calculated to ensure the reliability constraint, and the resource allocation of URLLC users is done iteratively.  
By varying the number of URLLC users, i.e., the URLLC service load, the URLLC packet reception rates under different methods are compared. As shown in Figure 3, the URLLC packet reception rate decreases significantly as the URLLC service load increases. That is because as more and more URLLC packets are accessed, the available resources obtained from puncturing are insufficient to accommodate all URLLC packets. As a result, to ensure the QoS of eMBB, some URLLC packets are rejected, leading to algorithm performance degradation. When the number of URLLC users is certain, the acceptance rate of the proposed scheme in this paper is higher; especially when the number of URLLC users is more, its superiority is more prominent.  
As shown in Figure 4, the objective optimization using the heuristic algorithm can complete the allocation task within one mini-slot. In contrast, the time used by the algorithm proposed in the literature [4] increases significantly with the number of URLLC, which is highly likely to violate the URLLC delay requirement. That is because the algorithm proposed in the literature [4] uses a general iterative approach, which will significantly degrade the performance as the number of iterations increases. In contrast, this paper uses a heuristic algorithm based on an intuitive or empirical construction. Its characteristic is to give a feasible solution for each instance of the combinatorial optimization problem to be solved within an acceptable computational time. Therefore, combined with Figures 3 and 4, the PF scheduling algorithm has a low URLLC packet acceptance rate and time complexity. In contrast, the algorithm proposed in the literature [4] has significantly lower performance and substantially higher latency as the URLLC load increases. Using the  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Value** \\ \hline Cell radius (r) & 300 m \\ The total bandwidth (B) & 20 MHz \\ RB bandwidth (BRB) & 180 kHz \\ The base station transmitting power (PgNB) & 46 dBm \\ URLLC maximum transmitting power (P\({}_{1}^{m}\)) & 23 dBm \\ eMBB maximum transmitting power (Peb) & 23 dBm \\ Number of subcarriers per RB & 12 \\ URLLC transmission interval (sTTI) & 0.1443 ms \\ eMBB transmission interval (TTI) & 1 ms \\ \hline \hline \end{tabular}
\end{table}
Table 1: Parameter Settings.  
heuristic algorithm takes less time and has lower time complexity, which is more suitable for eMBB and URLLC coexistence scenario applications.