# Multi-Connectivity for Multicast Video Streaming in Cellular Networks
## 7 Simulations
Figure 3: Average number of packets successfully delivered using MC multicasting as a function of an increasing number of users under centralized (Algorithm 3) and distributed (Algorithm 4) resource allocation algorithms. Figure 5a,b plot the average number of users left unserved in a cell per sub-frame as a function of an increasing number of users and the cell radius, respectively. The number of users left unserved increases as the number of users and cell radius increase. The performance gap between MC and SC multicasting also increases as the number of users increases. We observe that in the absence of multi-connectivity, nearly thrice as many users are left unserved. In Figure 6a,b, we compare the performances of MC and SC multicasting while serving a real-time video stream. To generate realistic video traffic patterns, we used traces of a video of the Tokyo Olympics that has 133,121 packets (obtained from [[http://trace.eas.asu.edu](http://trace.eas.asu.edu)]([http://trace.eas.asu.edu](http://trace.eas.asu.edu)), (accessed on 20 March 2023)) [11]. For these simulations, the rate of transmission varied every sub-frame according to the size of the video frame being transmitted. We ran the simulations for the duration of the video stream (133,121 sub-frames) and then averaged the results over the entire duration of the transmission. From Figure 6a, we observe that MC multicasting delivers around 8000 more packets successfully than SC multicasting. From Figure 6b, we observe that 10-20 more UEs are left unserved under SC multicasting than under MC multicasting. The performance gap between the two increases as the number of UEs in the system increases. Figure 5: Comparisons of the average number of users left unserved under SC and MC multicasting. Resource allocation was performed using the proposed CGA algorithm (Algorithm 3), and the results are plotted as a function of (**a**) an increasing number of users and (**b**) increasing cell radii. Figure 6: Comparisons of (**a**) the average number of packets successfully delivered (out of 133,121) and (**b**) the average number of users left unserved under SC and MC multicasting while transmitting a real-time video stream. Realistic video traffic patterns were generated using traces of a video of the Tokyo Olympics [11]. In Figure 7,b, we compare the performance of MC multicasting with that of MBSFN transmissions. Since MBSFN requires transmitting the content over the same PRB in all the cells, we chose the PRB that serves the maximum number of UEs in the entire system. We used traces from a real video stream (Tokyo Olympics [11]) to generate realistic video traffic patterns in these simulations as well. We observe that MC multicasting performs remarkably better than MBSFN. It succeeds in delivering a significantly greater number of packets successfully and is also able to serve many more UEs than MBSFN. These results validate our claims that MC multicasting can provide the benefits of MBSFNs while eliminating the need for strict synchronization. In fact, as observed in Figure 7, MC multicasting outperforms MBSFN by large margins. These simulation results clearly indicate that using multi-connectivity results in significant performance enhancements in multicast systems. The flexibility of potentially receiving content from multiple base stations results in more users being served and in reduced packet loss as well. Thus, MC multicasting has tremendous potential for use in video streaming services. It can help alleviate the burden on network resources while serving a larger number of users simultaneously.