Speaker
Description
Fifth-generation (5G) systems have huge potentials in healthcare services, as they can allow to enhance effectiveness of treatments, accessibility to medical care, and quality of life for patients. The installation of 5G non-public networks seems to be very suitable for healthcare environments. However, due to 5G signal characteristics, an optimization study is necessary before introducing them in clinical practice to ensure network service continuity and to avoid any possible interferences with medical devices. Ray tracing is a very promising technique for the prediction of electromagnetic field levels generated by 5G systems. In this paper we present a ray tracing study on a real hospital-case scenario, assuming the installation of a class E2 5G non-public network operating at 26 GHz. The presented work is focused on pointing out the main potentials and limitations of this typology of network in healthcare ecosystem, both from coverage and from compliance with exposure limits point of view. Two different proprietary tools are involved in this evaluation and a comparison between their outcomes will show the robustness and the reliability of the employed ray tracing tools in these scenarios. Moreover, a comparison with results obtained using a class E2 5G non-public network operating at 3.7 GHz will be presented, highlighting differences and similarities of the two case studies.
