Spatial spectrum and energy efficiency of random cellular networks
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 …
systems. In this paper, we propose new spatial spectrum and energy efficiency models for …
Relay-assisted D2D underlay cellular network analysis using stochastic geometry: Overview and future directions
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 …
capacity requirements of the fifth-generation wireless systems (5G). It has diverse …
Channel quality prediction based on Bayesian inference in cognitive radio networks
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 …
paper. First, the spectrum sensing process is modeled as a Non-Stationary Hidden Markov …
Cooperative relay selection in cognitive radio networks
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 …
emerging wireless applications in recent years. While many existing works assume that the …
Decentralized federated learning over slotted aloha wireless mesh networking
Federated Learning (FL) presents a mechanism to allow decentralized training for machine
learning (ML) models inherently enabling privacy preservation. The classical FL is …
learning (ML) models inherently enabling privacy preservation. The classical FL is …
Flcc: Efficient distributed federated learning on iomt over csma/ca
Federated Learning (FL) has emerged as a promising approach for privacy preservation,
allowing sharing of the model parameters between users and the cloud server rather than …
allowing sharing of the model parameters between users and the cloud server rather than …
Optimal spectrum sensing interval in cognitive radio networks
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 …
spectrum at the beginning of each time slot. A closer look at the network activities of a …
Decentralized federated learning on the edge over wireless mesh networks
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 …
leading to the emergence of federated learning as a novel distributed machine learning …
Distributed and asynchronous data collection in cognitive radio networks with fairness consideration
As a promising communication paradigm, Cognitive Radio Networks (CRNs) have paved a
road for Secondary Users (SUs) to opportunistically exploit unused licensed spectrum …
road for Secondary Users (SUs) to opportunistically exploit unused licensed spectrum …
Defending against cooperative attacks in cooperative spectrum sensing
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 …
either waste of spectrum or harmful interference to primary users. To improve accuracy …