  The Device-to-Device (D2D) communication principle is a key enabler of direct
localized communication between mobile nodes and is expected to propel a
plethora of novel multimedia services. However, even though it offers a wide
set of capabilities mainly due to the proximity and resource reuse gains,
interference must be carefully controlled to maximize the achievable rate for
coexisting cellular and D2D users. The scope of this work is to provide an
interference-aware real-time resource allocation (RA) framework for relay-aided
D2D communications that underlay cellular networks. The main objective is to
maximize the overall network throughput by guaranteeing a minimum rate
threshold for cellular and D2D links. To this direction, genetic algorithms
(GAs) are proven to be powerful and versatile methodologies that account for
not only enhanced performance but also reduced computational complexity in
emerging wireless networks. Numerical investigations highlight the performance
gains compared to baseline RA methods and especially in highly dense scenarios
which will be the case in future 5G networks.
