# Performance Model for Video Service in 5G Networks
## 3 Approaches
### Network Design Approach
We used link curve to determine how many data are transmitted for each scheduled UE and the transmitted data will be removed from its queue. For a UE, we record its time to receive a video frame and if after a period of time (i.e., 100 ms of delay budget) the frame is still not being completely transmitted, a packet drop will be recorded. ## 5 Simulation Results

Figure 6 shows the comparison of the bandwidths required for different IC approaches for the virtual reality service (S1) with a 25 M data rate, 20 ms delay budget (90 frames per second (FPS) with

Figure 5: \(2\times 2\) MIMO link curve [23]. 11 ms frame delay and 9 ms transmission delay), and a packet loss rate of \(10^{-3}\). This scenario simulated a network with a cell radius of 100 meters (ISD = cell radius \(\times\)\(\sqrt{3}\)), 10/20/30 UEs per sector, 4 beams to horizontally cover the sector area, a maximum 3 sectors per cluster, and a maximum of 4 MU-MIMO users per sector. Ten simulations were run with different random seeds, and the results were averaged. The baseline approach is an approach in which no interference coordination is performed. The coordinated beamforming IC approach (BFIC) is a one-level IC approach with intra-cluster interference coordination only. The proposed two-level IC approach, together with the BFIC approach, show improvement in the required bandwidth compared to that of the baseline approach. The two-level IC-P1 approach achieved the minimum required bandwidth, but the two-level IC-P2 approach was worse than the BFIC-P2 approach because of the capacity loss the approach caused. Figure 6: Different IC approaches for the Virtual Reality service. Sub-figure **(a)** shows IC-P1 (UIC) approaches and sub-figure **(b)** shows IC-P2 (GIC) approaches

Figures 7 and 8 are similar to Figure 6. Figure 7 is a scenario for an interactive gaming service (S2), with a 5 M data rate, 100 ms delay budget (40 FPS, 20 ms delay for frame encoding and decoding, and 80 ms transmission delay), and a packet loss rate of \(10^{-3}\). Figure 8 shows a scenario for a mix of conversational video service (S3) and non-conversational video service (S4) with 50% loading each. Both services had the same 5 M data rate and a packet loss rate of \(10^{-3}\), but different delay budgets (150 ms for S3 with a 130 ms transmission delay, and 300 ms for S4 with a 280 ms transmission delay). Figures 7 and 8 show that the two-level IC-P1 approach achieved the minimum required bandwidth. Selecting the two-level IC-P1 approach that achieved the minimum required bandwidth, Figure 9 shows the scatter plot of 200 drops with different random seeds. For simplicity, we fixed the cell radius to 100 m, the average number of users per sector at 10, the beams to cover the sector area at 8, and the service as S2 (interactive gaming service). For network design, as explained in Section 3, for each data point (\(s\), \(u\), \(b\), \(isd\), \(dis\), and varT), the maximum required bandwidth is calculated to create the performance model. Figure 8: Different IC approaches for the Mixed Video Traffic service. Sub-figure (**a**) shows IC-P1 (UIC) approaches and sub-figure (**b**) shows IC-P2 (GIC) approaches. Figures 10-12 show the network design performance model, simplified by fixing the traffic demand variance \(varT\) and the number of beams to 8. The number of UE and the ISD (or the cell radius) were varied with discrete values, and for each data point of (\(u\) and \(isd\)), 50 drops were run. Figure 13 shows an example of design solution using the performance models in Figures 10-12. The SLA requirements include varied UE density (we assume the same UE density among all three scenarios, i.e., N UE per sector for S1, N UE per sector for S2, and N UE per sector for S3 plus S4) and total available bandwidth of 1 GHz. A network design solution was to find an ISD in which the bandwidth was shared among services. In all three scenarios specified in Figures 6-8, the UE covered by the sites fulfilled their QoS requirements. Figure 14 shows the SLA violation rate using a performance model.