Fifth Generation (5G) Millimeter Wave spectrum (mmWave) cellular networks are particularly interesting within the Industry 4.0 paradigm. mmWaves provide flexibility to the industrial use case, as well as enable specific application requirements, e.g. robots needing high data rates and low latency communication. Nevertheless, coverage is severely limited by propagation, requiring the use of beamforming to overcome this by steering transmissions towards specific directions. Reliability is a key requirement as well, and requires, e.g, seamless beam switching during movement. Here, the resulting directivity of the antennas makes the beam switching procedures key to maintain the connectivity as the users move by. The present work analyzes the beam switching performance in a real-world indoor industrial scenario with high clutter, and identifies conditions based on radio KPIs and location information that will enrich the beam switching criteria.

Failure management is one of the key aspects in cellular networks. 5G technology is introducing several novel features that will cause the occurrence of new problems in the network. The objective of the present work is to identify which features may lead to potential network failures. In this way, a subset of problems has been identified and categorized. They were analyzed in order to know how they are in line with 3GPP specifications. Based on this, the present work proposes a novel failure management approach, applying it for failure simulation and impact analysis over the network performance.

Cellular networks are moving to fully automated schemes to minimize human intervention and maximize efficiency. This is what is called the Zero Touch networks paradigm. Until now, such management has been based on Drive Test results together with network-side metrics. However, this approach is clearly insufficient to achieve Zero Touch due to the complexity and high cost of collecting user side data in an increasingly vast and heterogeneous infrastructure. In this regard, the present work describes a novel framework for Zero Touch cellular networks that exploits the advantages of integrating User Equipment metrics. The suitability of the proposal has bee verified using data acquired from a commercial mobile network, achieving promising results through the use of traditional as well as User Equipment side metrics.