Nowadays, machine learning (ML), which is one of the most rapidly growing technical tools,
is extensively used to solve critical challenges in various domains. Vehicular ad hoc network …

Although spectrum sensing is commonly used in modern wireless communications to
determine spectrum resources, the rapid development of wireless communications has …

In this paper, multiple machine learning-enabled solutions are adopted to tackle the
challenges of complex sensing model in cooperative spectrum sensing for non-orthogonal …

The continuous growth of demand experienced by wireless networks creates a spectrum
availability challenge. Cognitive radio (CR) is a promising solution capable of overcoming …

The main objective of cognitive radio network is to provide flexible spectrum management,
by permitting the secondary users (SUs) to temporarily access the licensed spectrum in the …

Recommender systems provide information and items that match a user's preference. This
study proposes hybrid recommender models that use content-based filtering and latent …

Spectrum sensing in a large-scale heterogeneous network is very challenging as it usually
requires a large number of static secondary users (SUs) to obtain the global spectrum states …

Smart cities are claimed to be smart if the new technologies are capable of providing desired
sustainable outcome. The sustainable properties of smart city applications require less …

In vehicular ad-hoc network (VANET), the reliability of communication is associated with
driving safety. However, research shows that the safety-message transmission in VANET …

The optimal spectrum access strategy is investigated for multi-user multi-channel scenario in
cognitive radio networks. At first, an online learning method based on Dirichlet Process is …