  The objective of this study is to jointly analyze the data rate and
electromagnetic field (EMF) exposure in urban environments. Capitalizing on
stochastic geometry (SG), a network level analysis is performed by modelling
these environments via Manhattan Poisson line processes (MPLP). Using this
framework, a number of performance metrics are derived: first moments, marginal
distributions and joint distributions of the data rate and exposure. In
addition, the original Manhattan model is generalized to include advanced
features: corner diffraction, presence of potential blockages in streets, and
users positioned at crossroads. As a second approach, deterministic ray tracing
(RT) is utilized to compute the same metrics. The two methods are shown to
provide close results on the condition that the model parameters are coherently
selected. Furthermore, the numerical results enable to gain insight into
several aspects: the role of the propagation mechanisms in the performance
metrics, existing trade-offs between the rate and exposure requirements, as
well 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. Copyright
may be transferred without notice, after which this version may no longer be
accessible)
