It is a great challenge to evaluate the network performance of cellular mobile communication
systems. In this paper, we propose new spatial spectrum and energy efficiency models for …

Device-to-Device (D2D) communication is one of the enabling technologies for meeting the
capacity requirements of the fifth-generation wireless systems (5G). It has diverse …

The problem of channel quality prediction in cognitive radio networks is investigated in this
paper. First, the spectrum sensing process is modeled as a Non-Stationary Hidden Markov …

Federated Learning (FL) presents a mechanism to allow decentralized training for machine
learning (ML) models inherently enabling privacy preservation. The classical FL is …

The benefits of cognitive radio networking (CRN) have been well recognized with the
emerging wireless applications in recent years. While many existing works assume that the …

The rapid growth of Internet of Things (IoT) devices has generated vast amounts of data,
leading to the emergence of federated learning as a novel distributed machine learning …

Traditional spectrum sensing methods require that a secondary user (SU) senses the
spectrum at the beginning of each time slot. A closer look at the network activities of a …

As a promising communication paradigm, Cognitive Radio Networks (CRNs) have paved a
road for Secondary Users (SUs) to opportunistically exploit unused licensed spectrum …

Accurate spectrum sensing is important in cognitive radio networks. False sensing results in
either waste of spectrum or harmful interference to primary users. To improve accuracy …

Constructive interference (CI) enables concurrent transmissions to interfere non-
destructively, so as to enhance network concurrency. In this paper, we propose deliberate …