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The objective of this study is to jointly analyze the data rate andelectromagnetic field (EMF) exposure in urban environments. Capitalizing onstochastic geometry (SG), a network level analysis is performed by modellingthese environments via Manhattan Poisson line processes (MPLP). Using thisframework, a number of performance metrics are derived: first moments, marginaldistributions and joint distributions of the data rate and exposure. Inaddition, the original Manhattan model is generalized to include advancedfeatures: corner diffraction, presence of potential blockages in streets, andusers positioned at crossroads. As a second approach, deterministic ray tracing(RT) is utilized to compute the same metrics. The two methods are shown toprovide close results on the condition that the model parameters are coherentlyselected. Furthermore, the numerical results enable to gain insight intoseveral aspects: the role of the propagation mechanisms in the performancemetrics, existing trade-offs between the rate and exposure requirements, aswell as the impact of the user location (at a crossroad or in a single street).  (This work has been submitted to the IEEE for possible publication. Copyrightmay be transferred without notice, after which this version may no longer beaccessible)

Joint data rate and EMF exposure analysis in Manhattan environments: stochastic geometry and ray tracing approaches