Hybridization of GNSS and 5G Measurement for Assured Positioning, Navigation and Timing

Positioning, Navigation and Timing (PNT) services based on the Global Navigation Satellite System (GNSS) have a number of known drawbacks that makes them prone to suffer a disruption. These flaws can be exploited to disable this service in critical infrastructures. Therefore, the hybridization of GNSS and 5G measurements enabling Assured PNT (APNT) services is growing up and gaining attention by governmental bodies. 5G signals emitted by terrestrial networks and by Low Earth Orbit (LEO) satellites can complement GNSS enhancing their reliability, security and accuracy. For example, the larger Signal-to-Noise Ratio (SNR) of a terrestrial system makes them more difficult to suffer a jamming attack as compared to GNSS signals. A joint data and positioning signal enhances the security and reliability of the APNT solution with, for example, the successful decoding of encrypted data could be used for system authentication. Moreover, a larger signal bandwidth increases the accuracy of the PNT solution. All of these benefits can be extracted from the 5G terrestrial and non-terrestrial networks that transmit the Positioning Reference Signal (PRS). The rationale for these benefits rely on the flexibility of this pilot signal in terms of bandwidth or symbols used for the APNT service. This paper aims to analyse how this flexibility can be optimized to achieve a specific level of accuracy, minimizing the resources used under certain constrains of bandwidth or latency. The results present the optimal parameters to design a 5G PRS waveform with a target scenario constrains. Then, we compare it with the GNSS service and how to benefit when using them in combination. Finally, the paper concludes with the future research lines proposing a joint communications and positioning system as a feedback or closed loop. In such scenario, the user achieved accuracy is sent back to the infrastructure, and using the dynamic PRS flexibility, the system increases or reduces the PRS resources in order to meet the user accuracy requirements.