## 5 Beyond 5G  
The evolution of expectations, and thus solutions, in cellular positioning remains unbroken--just as the emergence of commercial use cases such as factory automation, transportation, and logistics have shaped 5G positioning, advanced commercial applications of the future such as extended reality (XR) gaming, telemedicine, driverless vehicles, and autonomous industrial systems will largely influence the evolution of cellular networks beyond 5G [25; 69; 70; 71; 72; 73]. The 6G network will aim to satisfy the challenging requirements of these new applications based on its unprecedented technological advancements. These advancements include even higher frequency ranges, wider bandwidths, massive antenna arrays, intelligent surfaces, intelligent beam-space processing, AI and machine-learning-based techniques, sidelink solutions, architecture evolution, and beyond connectivity [25; 69; 70; 71; 72; 73; 74; 75]. These new technologies (as illustrated by Figure 6) will enhance legacy solutions through efficiency and cost optimization [25; 74], and open up new possibilities for 6G localization [25; 69; 70; 71; 73]. In order to satisfy the requirements of new technologies, networks beyond 5G will be forced to conform to even higher standards related to positioning, translating to possibly under 0.5 ms latency, up to eight nines reliability and down to centimeter-level positioning accuracy [72; 75; 76], or even sub-centimeter level relative-positioning accuracy [73]. The possible capabilities of 6G networks as opposed to 5G are summarized in Table 3.  
Figure 6: The enablers, new applications, and challenges of 6G [69]. In current 5G NR positioning, position estimation is based on three components: signal strength, which is often inaccurate because both the path loss of the radio channel and the exact gain of the transmitter and receiver chains are unknown, time-of-arrival, which is limited by the bandwidth of the Positioning Reference Signal (PRS), or angle measurements whose accuracy is limited by the size of the antenna array or the aperture [25]. Possible solutions to overcome these accuracy limitations on the way to 6G are carrier aggregation for positioning and carrier-phase based positioning [77]. Carrier aggregation aims to achieve a higher overall effective bandwidth by combining PRSs received on different carriers into one signal with a very high overall bandwidth [25]. Carrier-phase-based positioning methods [25] use a different approach in which the phase of the correlator output signal varies quickly with increasing propagation distance. One full phase cycle corresponds to one wavelength of the carrier signal. Since the carrier frequency is usually at least a factor of ten or more higher than the bandwidth, the achievable accuracy is about this factor higher, assuming that it is possible to measure a certain fraction of a full phase cycle [25]. The same principle is used in GNSS-RTK (Global Navigation Satellite System-Real Time Kinematic) to achieve centimeter accuracy [25]. All phase measurements need to be performed on the Line-Of-Sight (LoS) path--this requires advanced LoS/NLoS (Non-LoS) detection and separation methods. Standard support to identify NLoS paths and mitigate their impact on timing measurements is already part of the 17 th 3 GPP release, but this needs to be extended to phase measurements and higher accuracies [25]. Aside from accuracy, low latency is another critical factor for delivering effective positioning services in 5G and beyond [70]. The applications strongly related to positioning in 5G networks and beyond are associated with an increased level of automation, which requires the location of objects (such as automated vehicles) to be obtained at a millisecond level [25; 70; 74].