  In this paper, the problem of distributed resource allocation is studied for
an Internet of Things (IoT) system, composed of a heterogeneous group of nodes
compromising both machine-type devices (MTDs) and human-type devices (HTDs).
The problem is formulated as a noncooperative game between the heterogeneous
IoT devices that seek to find the optimal time allocation so as to meet their
quality-of-service (QoS) requirements in terms of energy, rate and latency.
Since the strategy space of each device is dependent on the actions of the
other devices, the generalized Nash equilibrium (GNE) solution is first
characterized, and the conditions for uniqueness of the GNE are derived. Then,
to explicitly capture the heterogeneity of the devices, in terms of resource
constraints and QoS needs, a novel and more realistic game-theoretic approach,
based on the behavioral framework of cognitive hierarchy (CH) theory, is
proposed. This approach is then shown to enable the IoT devices to reach a CH
equilibrium (CHE) concept that takes into account the various levels of
rationality corresponding to the heterogeneous computational capabilities and
the information accessible for each one of the MTDs and HTDs. Simulation
results show that the proposed CHE solution keeps the percentage of devices
with satisfied QoS constraints above 96% for IoT networks containing up to
10,000 devices without considerably degrading the overall system performance.
