Phd in AUTOMATIC CONTROL, BIOENGINEERING AND OPERATIONS RESEARCH

Thesis title: Network Control Systems for 5G Multi-Connectivity

This thesis aims to develop a network control framework when considering heterogeneous access network technologies. The scenario of interest is when several services are using a common shared and large-scale communication network and the users who are benefiting from these services have different connection requirements. The reason behind the need for a common network satisfying several service requirements at the same time, is the continuous transformation of physical infrastructures such as energy distribution, entertainment, communication, transportation, and many others, in Cyber-Physical Systems interacting with each other. This transformation increases the need of the different industries in the deployment of large-scale communication networks, to connect the high number of sensors and actuators integrated into the physical infrastructure, introducing the so-called Networked Control System. In this framework, when sensors and actuators are used to perform and act decision-making on large-scale systems, several problems introduced by the networking arises. In particular, when unpredictable and uncontrollable packet drop, latency, or data corruption occur, either between sensors or actuators and the autonomous decision-maker, the resulting control actions may perform undesired effects on the controlled physical system introducing instability. These problems can be considered during the autonomous decision-maker design, implying higher design and implementation complexity, that can degrade the performances concerning the controlled physical systems. Another solution is the development of an underlying network control able to provide the needed networking performances to the decision-maker as a service. This solution allows the decision-maker to see the network as a black box that meets its requirements. This network control problem can be faced considering different aspects because of the high number of problems that can be addressed to have an efficient and reliable network, one of the main problems to be addressed is resource allocation. This work deal with the resource allocation considering multi-connectivity, defined as the management of the network resources when the users can connect simultaneously to different access points, even belonging to different radio technologies, to satisfy users’ requirements, and considering network constraints and efficiency. Furthermore, in this work the reference network is the fifth-generation technology standard for broadband cellular networks, known as 5G Network, standardized by the 3GPP association. The 5G Network is designed to provide a general-purpose connectivity platform, considered as the key enabling technology to support markets such as automotive, energy, food and agriculture, city management, government, healthcare, manufacturing, and public transportation, through the digital transformation of their infrastructure and business processes, providing a large scale, efficient and reliable communication platform, able to satisfy several users’ requirements such as high reliability, ultra-low latency, high bandwidth, and mobility. The thesis presents the definition of network architecture, compliant with the 3GPP standards and able to accommodate multi-connectivity algorithms, and control algorithms able to manage the multi-connectivity considering both users’ requirements and network conditions, using either model-based and data-driven techniques, using centralized, distributed and hierarchical solutions, allowing the deployment of the control algorithms either in the cloud or at the edge of the network, on the basis of the resources and performances needed in each particular scenario.