# Inter-Beam Co-Channel Downlink and Uplink Interference for 5G New Radio in mm-Wave Bands +
## 5 Simulation Results
### Exemplary Comparison of MPM with 3 GPP Approach for DL Scenario  
In this section, we provide an example comparison of the proposed MPM-based approach with another solution. In our opinion, choosing a different propagation model that can be the basis for a similar analysis of the inter-beam interference level is not easy. It results from the fact that only a few propagation models make it possible to consider the parameters and patterns of antennas and the environmental scattering of signals occurring in a radio channel. The statistical model based on the 3 GPP standard [14] is one of them. Moreover, the choice of the 3 GPP model was dictated by three reasons. Firstly, the analysis carried out in this paper with the use of the MPM is based on TDLs defined in the same standard [14]. Secondly, in both simulators we considered the same antenna patterns created according to the 3 GPP recommendation [42]. Thirdly, we were able to use a proprietary simulator of the 3 GPP statistical model, which was developed in the MATLAB environment and is used for generating the results contributed to the 3 GPP, as an input to 5G standardization or research studies (e.g., [9; 44]). Exemplary interference comparison determined based on the MPM and 3 GPP model was carried out for the DL scenario and the distance \(D=100\) m. To obtain the average SIR, \(SIR_{\text{avg}}\), the Monte Carlo method with 1000 repetitions of statistical channel model realizations was used in the 3 GPP simulator. Based on the set of obtained results, confidence intervals for \(SIR_{\text{avg}}\) with the standard deviation \(\sigma_{SIR}\) were also determined. The same parameters as in Section 5.1 were adopted in the research. To compare the MPM and 3 GPP approaches, we ran the MPM simulator also in Monte Carlo mode for 1000 runs. Thus, the mean results, \(SIR_{\text{avg}}\), with the confidence intervals, \(SIR_{\text{avg}}\pm\sigma_{SIR}\), were determined. The results of the MPM and 3 GPP comparison for the DL scenario and the distance \(D=100\) m between the gNodeB and UE are illustrated in Figures 14 and 15 for LOS and NLOS conditions, respectively. Overall, we might conclude that the results are similar. The SIR results are more similar for LOS conditions (see Figure 14), where we may see characteristic extremes resulting from the use of the same gNodeB antenna pattern. In this case, both the maxima and the minima fall for the same separation angles. This is due to the presence of a direct path that enhances or reduces the influence of the pattern side lobes in certain directions relative to its main lobe (see Figures 4 and 5). Therefore, the optimal directions' selection for the adjacent beams in the gNodeB based on the MPM and 3 GPP approaches will be identical or very similar. In this case, we would like to emphasize that the MPM approach gives the possibility to obtain an average result from a single simulation, while the 3 GPP statistical model requires the time-consuming Monte Carlo methodology. Under NLOS conditions (see Figure 15), the dynamics of SIR changes is lower than for LOS conditions. The results for the MPM and the 3 GPP model show that the multipath  
Figure 14: SIR comparison between (**a**) MPM and (**b**) 3 GPP model for DL scenario, \(D=100\) m, and LOS conditions. Figure 15: SIR comparison between (**a**) MPM and (**b**) 3 GPP model for DL scenario, \(D=100\) m, and NLOS conditions. propagation environment for NLOS conditions and the lack of a direct path provide to minimize the impact of the transmitting antenna pattern lobes. Thus, the selection of optimal directions for the adjacent gNodeB beams should be made based on an analysis for LOS conditions. On the other hand, we would like to highlight that other propagation models available in the literature also indicate result differences with the 3 GPP model, e.g., [45; 46; 47; 48].