# A Modular Experimentation Methodology for 5G Deployments: The 5 GENESIS Approach
## 2 Background and Related Work
### Research on 5G KPI Testing and Validation  
Rigorous testing of 5G E2E solutions is still an emerging research topic, where we find a relevant gap. There are only a few papers that are devoted to this area. In the context of the TRIANGLE project, the work in [29] proposes a methodology in order to automate the control of all the elements in the E2E 5G network path, while [30] focuses on automating 5G apps. Both of the papers aim to test service level KPIs in a 5G E2E lab setup, while the 5 GENESIS methodology described in this paper is tailored for testing and validation in real 5G deployments. In the context of 5G field trials, several works provide ad-hoc solutions for specific use cases, scenarios, and KPIs. The authors in [31] study throughput for using 15 GHz band. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Main Component** & **Reference** & **Focus** \\ \hline \multirow{8}{*}{UE} & 3 GPP TS 38.521-3 [9] & 5 GNR UE RF conformance. NSA \\  & 3 GPP TS 38.521-1/2 [10, 11] & 5 GNR UE RF conformance. SA FR1/FR2 \\  & 3 GPP TS 38.521-4 [12] & 5 GNR UE RF conformance. Performance \\  & 3 GPP TS 38.523-1/2/3 [13; 14; 15] & 5 GNR UE protocol conformance \\  & 3 GPP TS 38.533 [16] & 5 GNR UE RRM conformance \\  & GCF/CTIA [17] & Battery consumption \\ RAN/Core & 3 GPP TS 28.552 [18] & RAN, 5 GC, and network slicing performance \\ RAN & 3 GPP TS 32.425 [19], TS 32.451 [20] & RRC aspects \\ NFV & ETSI GS NFV-TST 100 [22] & Testing of ETSI NFV blocks \\  & 3 GPP TR 37.901 [23], TR 37.901-5 [24] & 4G/5G throughput testing at application layer \\ E2E & 3 GPP TR 28.554 [26] & Slicing performance at network side \\  & NGMN [27] & eMBB and uRLLC (partial) KPI testing \\ Network elements & 3 GPP TS 32.404 [21] & Measurement templates \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Summary of standards for 5G testing and Key Performance Indicator (KPI) validation. In [32], the authors test throughput and latency in vehicular communications. The work presented in [33] analyses throughput, network energy efficiency, and device connection density. The work in [34] focuses on different methods for generating and evaluating the effect of interference. Moreover, large scale performance measurements on 5G operational networks and off-the-shelf UEs have been recently presented in [35; 36]. On the one hand, [35] covers a sub-6 GHz NSA deployment in a dense urban environment, revealing several insights on network coverage, handover mechanisms, UE energy consumption, and E2E throughput, latency, and application performance. On the other hand, [36] discusses throughput, latency, and application performance, along with handover operations, under four different US operators' networks, with three of them employing NSA deployment with mmWave 5G cells. The above papers provide valuable preliminary insights on 5G achievable performance; however, technology and KPI validation requires dedicated and fully controllable testing environments [3], in order to pinpoint specific causes for the observed performance levels, and ultimately guide towards focused optimized configurations. Our work contributes to these aspects by providing the definitions of E2E KPIs and of testing procedures for reliable performance assessment in dedicated environments. Several testbeds are being developed for supporting reliable experimentation, testing, and validation of 5G technologies, paradigms, and KPIs, as anticipated in Section 1. Among others, the 5G Test Network (5 GTN) presented in [37] integrates cellular access and core networks with SDN/NFV, cloud/edge computing, and Internet of Things (IoT) technologies. Targeting more specific use cases, [38] showcases NFV integration with Unmanned Aerial Vehicles (UAVs), while [39] presents a SDN-based cloud/edge computing platform for IoT management. IoT experimental testbeds for mMTC and low-power devices are also presented in [40; 41], while an open solution for E2E network slicing experimentation is given in [42].