  We study the detection and delay performance impacts of a feature-based
physical layer authentication (PLA) protocol in mission-critical machine-type
communication (MTC) networks. The PLA protocol uses generalized
likelihood-ratio testing based on the line-of-sight (LOS), single-input
multiple-output channel-state information in order to mitigate impersonation
attempts from an adversary node. We study the detection performance, develop a
queueing model that captures the delay impacts of erroneous decisions in the
PLA (i.e., the false alarms and missed detections), and model three different
adversary strategies: data injection, disassociation, and Sybil attacks. Our
main contribution is the derivation of analytical delay performance bounds that
allow us to quantify the delay introduced by PLA that potentially can degrade
the performance in mission-critical MTC networks. For the delay analysis, we
utilize tools from stochastic network calculus. Our results show that with a
sufficient number of receive antennas (approx. 4-8) and sufficiently strong LOS
components from legitimate devices, PLA is a viable option for securing
mission-critical MTC systems, despite the low latency requirements associated
to corresponding use cases. Furthermore, we find that PLA can be very effective
in detecting the considered attacks, and in particular, it can significantly
reduce the delay impacts of disassociation and Sybil attacks.
