## 4 Overview of Research Projects on AI/ML for Communications and Networking
### Europe--H2020 Research Framework
#### 4.1.2 5 genesis  
The 5 th generation E2E network, experimentation, system integration, and show-casing (5 GENESIS) is a 30-month 5G PPP project that started in July 2018 and received approximately EUR 16 million in contributions from the EU. The experimental facilities of 5 GENESIS include five testbeds that are used to implement several 5G-enabled use cases; see Table 6. To associate the measured KPIs with the network status, monitoring techniques and probes are implemented at several locations, network components and layers. In particular, data are collected at the end devices to measure the radio conditions and the device power consumption, at the RAN to evaluate resource availability and track the traffic load at the backhaul and fronthaul, at the core network to compute the processing load of various NFs, and at the edge/cloud to measure the CPU consumption and the utilisation of available computational resources. Then, ML is employed to process the large volumes of extracted data and identify hidden associations and correlations between the measured KPIs and the monitored network parameters and conditions. The measured correlations and causalities could be used at the real-time RIC, e.g., to design intelligent adaptive modulation and coding schemes, or may also lead to prescriptive analytics, e.g., making suggestions about how much additional computing power and storage should be deployed at the edge to meet a target KPI. \begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Use Cases** & **Scenarios** & **Mobility** \\ \hline Outdoor backhaul and fronthaul networks of fixed topology. & Long-range line-of-sight (LoS) rooftop point-to-point backhauling without RIS. & Stationary \\ \hline Street-level point-to-point and point-to-multipoint backhauling and fronthauling with RIS for non-LoS (NLoS). & Stationary \\ \hline Advanced NLoS connectivity based on meta-surfaces. & Indoor advanced NLoS connectivity based on meta-surfaces. & Stationary or low. \\ \hline Ad hoc connectivity in moving network topology. & Dynamic fronthaul and backhaul connectivity for mobile 5G access nodes and repeaters, e.g., using drones. & Stationary or low or moderate. \\ \hline LoS vehicle-to-vehicle (V2V) and vehicle-to-everything (V2X) connectivity. & Low or moderate. \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Use cases and corresponding scenarios considered by ARIADNE. \begin{table}
\begin{tabular}{l l l l l l l l} \hline \hline
**Use Cases** & **Latency** & **Coverage** & **Service Creation Time** & **Capacity** & **Availability** & **Reliability** & **User Density** & **Service Types** \\ \hline Big event & ✓ & ✓ & ✓ & & & & & eMBB \\ \hline Eye in the sky & ✓ & ✓ & ✓ & & & & eMBB, uRLLC \\ \hline Security as a service at the edge & ✓ & & ✓ & & & & All \\ \hline Wireless video in large scale event & & ✓ & & ✓ & ✓ & & & eMBB \\ \hline Multimedia mission critical services & ✓ & & & ✓ & ✓ & ✓ & eMBB, uRLLC \\ \hline MEC-based mission critical services & ✓ & & ✓ & ✓ & ✓ & & eMBB \\ \hline Maritime communications & ✓ & ✓ & & ✓ & ✓ & & eMBB \\ \hline Capacity on demand and rural IoT & ✓ & & & ✓ & ✓ & ✓ & eMBB, mMTC \\ \hline Massive IoT for large-scale public events & ✓ & & ✓ & ✓ & ✓ & & mMTC \\ \hline Dense urban 360 degrees virtual reality & ✓ & & ✓ & ✓ & ✓ & & eMBB \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Use cases associated with KPIs and 5G service types considered by 5 GENESES [117]. Let us consider the use case \"eye in the sky\" of 5 GENESIS where an UAV is controlled over 5G, where both the vehicle and the pilot are being served bydifferent cells. In that case, an uRLLC slice is required to route the joystick signals controlling the drone manoeuvres through the 5G core, and prioritise them over other applications with less stringent latency requirements. At the same time, an eMBB-with-controlled-latency slice must be also prioritised to route the real-time 4K video footage collected from the drone to the ground near the pilot through the 5G core [117].