  Low-latency communication is currently attracting significant attention due
to the emergence of mission-critical Internet of Things (IoT) applications and
content-centric services. A deep understanding of the delay performance is
essential for efficient wireless system design and end-to-end latency
guarantees. In this paper, we investigate the network-layer performance of
physical layer multi-antenna multicasting, i.e., when the same data is
simultaneously conveyed to multiple users. We provide a statistical
characterization of the service process in terms of its Mellin transform and
derive probabilistic delay bounds using tools from stochastic network calculus.
Furthermore, using extreme value theory, we characterize the service process
for very large number of users and derive scaling laws as the number of
antennas and/or users is taken to infinity. Our results can be used for system
dimensioning to guarantee the delay requirements in wireless multicast
networks.
