One of the key drivers for next-generation mobile communications is the support of the Internet of Things (IoT), with billions of objects connected to the Internet and very low latency. The 5G technology will support the realization of smart cities, smart environments, and big data applications. Within the 5G framework, the terrestrial services can be augmented with the development of Non-Terrestrial Networks (NTN) composed of many ‘layers’ including mega-LEO satellite constellations, High Altitude Stations (HAPs), and Unmanned Aerial Vehicles (UAVs). This lesson investigates the integration of satellite technology and IoT, considering different architectures and sensor technologies as NB-IoT, LoRa/LoRaWAN, and SigFox. These architectures will also envisage UAVs to collect massive data from remote areas and the possibility to connect via 5G satellite access to the Internet. Applications are possible in fire alarm detection, smart agriculture, animal tracking, plant disease control, environmental monitoring, just to name a few.

A new generation of services and applications is emerging that require lower latency, better reliability, large connections, and increased energy efficiency. These market opportunities and requirements are uniquely addressed by 5G's advanced features. Among the applications supported by Ultra-Reliable Low-Latency Communication (URLLC) are industrial internet, smart grids, remote surgery, and intelligent transportation systems. Aside from URLLC, Time-Sensitive Networking (TSN) also allows control and prioritization of Ethernet data streams. In order to achieve real-time capabilities, a variety of individual requirements, such as bandwidth guarantees, time synchronization, and low latency, are taken into account. The purpose of this talk was to shed light on different aspects of URLLC and TSN through the use of V2X as an example.

6G wireless solutions need to meet the anticipated demands of Machine-to-Machine (M2M) communications with the total number of devices expected to be about 26 billion in 2026 according to Ericsson Mobility Report. The wide variety of the requirements of massive M2M scenarios in terms of energy, reliability, delay and throughput, and the inclusion of a new spectrum of control applications, such as extended reality, remote surgery, autonomous vehicle platoons, increase the complexity of M2M system design significantly. This high complexity can only be handled by developing artificial intelligence (AI) based communication techniques, technologies and architectures while addressing the semantics of the control systems. In this talk, I will introduce extreme value theory-based channel modeling and communication techniques detecting rare events in ultra-reliable communication together with federated learning techniques for channel estimation.