# Joint User-Slice Pairing and Association Framework Based on H-NOMA in RAN Slicing
## 5 Results
### Simulation Results  
Most research projects on the coexistence between eMBB and uRLLC concur that the ratio of uRLLC to eMBB UEs is double per cell [15,54,58]. So, we assign the quota of U-S. P algorithm as \(\widetilde{\Theta}=2\). Thus, the paired uRLLC UE superimposes with an eMBB for \(\rho_{bl}=3\) mini slots. The number of eMBB UEs and uRLLC UEs are 25 and 50, respectively [15,54]. The minimum required rate levels of eMBB and uRLLC UEs are 4 and 0.5 Mbps, respectively. The submitted algorithm's effectiveness is compared with the Early Acceptance algorithm (EAA)-based matching game, Max-SINR, and Greedy algorithm (GA). All these algorithms are displayed in both cases of SINR \(\Gamma_{be}^{nm}>\Gamma_{bl}^{nm}\) and \(\Gamma_{bl}^{nm}>\Gamma_{be}^{nm}\), for different techniques (H-NOMA, OMA & Puncturing). We show the total DL throughput of uRLLC UEs with the different numbers of uRLLC when \(\Gamma_{be}^{nm}>\Gamma_{bl}^{nm}\) and \(\Gamma_{bl}^{nm}>\Gamma_{be}^{nm}\), in Figure 5 respectively. When uRLLC UEs grow, the uRLLC overall throughput rises in all schemes. In UE-slice association and pairing operations, uRLLC UEs are more interested in latency and reliability than DL data rate. We observe how similar the two shapes are, where our submitted H-NOMA algorithms are still superior in performance over DAA- PUNC and OMA strategies. To explain it, a uRLLC UE is paired with an eMBB UE and occupies the eMBB's PRBs per \(\rho_{bl}\) mini slots. As for using the puncturing technique, an uRLLC UE is overlapped with an eMBB UE and occupies an eMBB's PRBs per one mini slot. Meanwhile using the OMA technique, each uRLLC UE takes up one PRB per long TTI. \begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Value** \\ \hline Transmit power of macro-BS & 46 dBm \\ Transmit power of pico-BS & 33 dBm \\ Backhaul bandwidth & 40 MHZ \\ Backhaul timeslot & 25 μs \\
5 GRAN bandwidth & 20 MHz \\ Number of PRBs & 100 \\ Inter-site distance & 500 m \\ Pathloss between MBS and device & \(128.1+37.6*\log(d)\) \\ Pathloss between SBS and device & \(140.7+36.7*\log(d)\) \\ device & \([1-4]\) Mbps \\ eMBB-rate threshold & \([0.1-1.6]\) Mbps \\ uRLLC rate threshold & 4-QAM, 64 QAM for uRLLC and eMBB, respectively \\ uRLLC packet size & \([32-256]\) bytes \\ PHY numerology & 15 kHz subcarrier spacing;12 subcarriers per PRB;2-OFDM symbols TTI (0.143 ms) \\ HARQ & Asynchronous HARQ with chase combining, and 4 TTI round trip time; \\  & Max 6 HARQ retransmissions. \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Simulation Parameters. After documenting our idea to distribute power among various users' PRB, it is time to display the other outputs and meet the goals of this study; as shown in Figure 6, the DL average throughput of eMBB UEs is against the number of uRLLC UEs. The average throughput of eMBB UEs falls as the number of uRLLC UEs grows. Even though the DL data rate is not an appealing attachment and pairing metric for uRLLC UEs, it suggests that UEs are vying to associate and pair with the best elected BSs based on their preference lists. The proposed algorithm and EAA-NOMA consider the QoS requirements for eMBB UEs during the association process. Thus, the minimum required DL data rate for eMBB UEs can be achieved, as seen in Figure 6. However, the suggested approach, which incorporates the QoS requirements for eMBB UEs throughout the association and pairing operations, has the lowest rate of loss for eMBB service and outperforms EAA-NOMA, particularly at many uRLLC UEs. This happens because EAA-NOMA does not achieve the best optimum solution since it allows the highest preference list to associate and pair until the system capacity is complete, but the eMBB UEs' minimum wanted DL data rate is assured; thus, not achieving the spirit of cooperation, which is based on a matching game. Without considering eMBB UE rate needs and the available PRBs at each BS, the performance of both Max-SINR and GA is worse than the proposed algorithm. In Max-SINR, most of the users are associated with MBS.