  Device-to-device (D2D) communications is one of the key emerging technologies
for the fifth generation (5G) networks and beyond. It enables direct
communication between mobile users and thereby extends coverage for devices
lacking direct access to the cellular infrastructure and hence enhances network
capacity. D2D networks are complex, highly dynamic and will be strongly
augmented by intelligence for decision making at both the edge and core of the
network, which makes them particularly difficult to predict and analyze.
Conventionally, D2D systems are evaluated, investigated and analyzed using
analytical and probabilistic models (e.g., from stochastic geometry). However,
applying classical simulation and analytical tools to such a complex system is
often hard to track and inaccurate. In this paper, we present a modeling and
simulation framework from the perspective of complex-systems science and
exhibit an agent-based model for the simulation of D2D coverage extensions. We
also present a theoretical study to benchmark our proposed approach for a basic
scenario that is less complicated to model mathematically. Our simulation
results show that we are indeed able to predict coverage extensions for
multi-hop scenarios and quantify the effects of street-system characteristics
and pedestrian mobility on the connection time of devices to the base station
(BS). To our knowledge, this is the first study that applies agent-based
simulations for coverage extensions in D2D.
