Tecniche di Elaborazione dei Segnali per la Protezione dei Segnali GNSS e delle Reti URLLC.

Wireless communications have evolved rapidly during the last 20 years. Nowadays, not only people communicate with each other, but also people communicate with machines and also machines communicate with each other. Therefore, there exist huge communication networks and the usage of these networks have grown exponentially. In order to support these intense demands, research should develop innovative but also realistic technologies. While developing new technologies, it is necessary that the vulnerabilities of these technologies are investigated. In this context, the aim of this Thesis is the proposal of signal processing techniques for the protection of global navigation satellite system (GNSS) signals and mobile networks, with particular focus to ultra-reliable low-latency communications (URLLC). GNSS-dependent positioning, navigation, and timing synchronization procedures have a significant impact on everyday life. Therefore, such a widely used system increasingly becomes an attractive target for illicit exploitation by terrorists and hackers for various motives. As such, anti-spoofing and anti-jamming algorithms have become an important research topic within the GNSS discipline. As a first contribution, this Thesis provides the performance evaluation of i) signal quality monitoring (SQM) techniques for anti-spoofing and ii) an adaptive notch filter for anti-jamming, both implemented in a security-oriented GNSS software package. Then, the problem of detecting spoofing attacks for a GNSS receiver in space orbiting around the Earth is considered and a solution via fusion of consistency metrics is proposed. Security has been one of the main drivers also in the design of the fifth generation (5G) of mobile communication systems by the 3rd Generation Partnership Project (3GPP), however with focus only at high layers to guarantee authentication, privacy and data integrity. On the other hand, jamming attacks for denial of service are a rising threat which can severely compromise the system performance, in particular in Industry 4.0 scenarios. This Thesis proposes a defense mechanism based on pseudo-random blanking of subcarriers with orthogonal frequency division multiplexing (OFDM) and designs a detector by applying the generalized likelihood ratio test (GLRT) on those subcarriers. The performance are evaluated against a smart jammer in single-cell single-user uplink scenario with additive white Gaussian noise (AWGN) and Rayleigh channel models. Then, this work is extended to investigate the problem of jamming detection and mitigation in a more realistic indoor factory deployment, where also a jamming mitigation with frequency hopping and random scheduling of user equipments (UEs) is proposed.