# A Modular Experimentation Methodology for 5G Deployments: The 5 GENESIS Approach
## 5 Experimental Setup
### ED Definition
In parallel, the UDP throughput is close to its PDCP counterpart at the experiment kick-off, and then it shows a decreasing trend over the experiment duration, resulting in a difference up to 10 Mbps for the extreme values in the final iterations. These are both unexpected behaviors, repeatedly detected on the devices under test, which call for further inspection and analysis. As highlighted by these results, the statistical analysis that is currently supported in the methodology enables quantifying KPI trends, validating nominal values, and detecting possible malfunctions and anomalies leading to performance issues. We are currently working on embedding further ML-based analytical functionalities in the methodology, which could provide more insights while potentially pinpointing the root cause of the observed performance. This would ultimately lead to the introduction of enhanced schemes for improving cross-layer configurations and performance across the 5G system. Figure 5: Experiment 2: RTT per-iteration statistics for TC_RTT test case, in SC_LoS_PS (PS active) and SC_LoS (PS inactive) scenarios and using UE_1. Figure 6a reports per-iteration statistics of UDP and PDCP throughput for both devices. As already analyzed in Experiment 1, we observe a UDP throughput of about 180 Mbps for UE_1 (Figure 6a). Interestingly, we see instead a PDCP throughput of around 271 Mbps, close to the theoretical maximum calculated in Section 5.3. Hence, under higher data rates possibly sustained by good coverage (i.e., LoS), UE_1 shows a quite constant and rather significant throughput drop while moving at application level. When considering UE_2 (Figure 6a), we see that the PDCP throughput stabilizes at a slightly lower value when compared to UE_1 (around 267 Mbps). In parallel, the UDP throughput is close to its PDCP counterpart at the experiment kick-off, and then it shows a decreasing trend over the experiment duration, which results in a difference up to 10 Mbps for the extreme values in the final iterations. These are both unexpected behaviors, repeatedly detected on the devices under test, which call for further inspection and analysis. The statistical analysis currently supported in the methodology enables quantifying KPI trends, validating nominal values, and detecting possible malfunctions and anomalies leading to performance issues, as highlighted by these results. We are currently working on embedding further ML-based analytical functionalities in the methodology, which could provide

Figure 6: Experiment 3: UDP and PDCP Throughput per-iteration statistics for TC_THR_UDP test case and SC_LoS_PS scenario. Results for UE_1 and UE_2 are reported in (**a**,**b**), respectively. more insights while potentially pinpointing the root cause of the observed performance. This would ultimately lead to the introduction of enhanced schemes for improving cross-layer configurations and performance across the 5G system. ## 7 Conclusions

In this paper, an open and flexible experimentation methodology for 5G KPI validation is introduced. This methodology overcomes the need for an end-to-end systematic experimentation methodology that allows properly defined and repeatable experiments. Such a methodology brings a key step towards a reliable and fair benchmarking of 5G services and applications. The methodology has been applied in order to calculate the maximum achievable throughput and the latency in 5G NR scenarios. In particular, three different scenarios have been designed and the ability of the methodology has been demonstrated to (a) validate different KPIs under heterogeneous network scenarios, (b) quantify the impact of specific network configurations on the performance, and (c) pinpoint issues in off-the-shelf 5G devices. Additionally, one of the designed scenarios has enabled to reach a minimum latency of 10 ms via activation of proactive scheduling mechanisms. This gives key insights on how to reach low latency in 5G deployments based on Release 15, which is focused on eMBB use cases.