Characterization of 5G mmWave High-Accuracy Positioning Services for Urban Road Traffic

The ongoing development towards autonomous traffic requires detailed context information, including highly accurate position estimates. The 5G standard has therefore extended its feature support for positioning and defined six service levels (SLs) to cater to the various commercial use cases. User positioning at millimeter-waves (mmWaves) is considered particularly promising due to the inherent support for angle measurements and the contiguous broad bands. However, in the literature, a comprehensive classification of the achievable SLs with different positioning algorithms under different parameter measurement errors is missing. Based on ray-tracing data, we find that only the lower SLs can be achieved in an urban scenario, whereas SLs 4 to 6 are hard to meet due to the high availability requirements. For such use cases, hybrid positioning is needed to shorten the tail of the error distribution further: We show that positioning with a single base station (BS) is particularly well-suited because the identified network time synchronization problem is bypassed, thus attaining high accuracy at low overhead. Service availability can be improved further by integrating satellite-based estimates.