Spectrum sensing for cognitive radio: Recent advances and future challenge
Spectrum Sensing (SS) plays an essential role in Cognitive Radio (CR) networks to
diagnose the availability of frequency resources. In this paper, we aim to provide an in-depth …
diagnose the availability of frequency resources. In this paper, we aim to provide an in-depth …
Spectrum sensing in cognitive radio networks and metacognition for dynamic spectrum sharing between radar and communication system: A review
SK Agrawal, A Samant, SK Yadav - Physical Communication, 2022 - Elsevier
The massive growth in mobile users and wireless technologies has resulted in increased
data traffic and created demand for additional radio spectrum. This growing demand for …
data traffic and created demand for additional radio spectrum. This growing demand for …
Deep CM-CNN for spectrum sensing in cognitive radio
One of the key problems in spectrum sensing is to design the test statistic. Existing methods
generally exploit the model-based features as the test statistic, such as energies and …
generally exploit the model-based features as the test statistic, such as energies and …
CR-IoTNet: Machine learning based joint spectrum sensing and allocation for cognitive radio enabled IoT cellular networks
In recent years, the Internet of Things (IoT) paradigm has gained much popularity due to its
potential ability to integrate the physical world with the digital world. However, this digital …
potential ability to integrate the physical world with the digital world. However, this digital …
A novelty of hypergraph clustering model (HGCM) for urban scenario in VANET
MK Jabbar, H Trabelsi - IEEE Access, 2022 - ieeexplore.ieee.org
A vehicular ad hoc network is a dynamic and constantly changing topology that requires
reliable clustering to prevent connection failure. A stable cluster head (CH) prevents packet …
reliable clustering to prevent connection failure. A stable cluster head (CH) prevents packet …
Deep learning-driven opportunistic spectrum access (OSA) framework for cognitive 5G and beyond 5G (B5G) networks
The evolving 5G and beyond 5G (B5G) wireless technologies are envisioned to provide
ubiquitous connectivity and great heterogeneity in communication infrastructure by …
ubiquitous connectivity and great heterogeneity in communication infrastructure by …
An overview of deep reinforcement learning for spectrum sensing in cognitive radio networks
Deep reinforcement learning has recorded remarkable performance in diverse application
areas of artificial intelligence: pattern recognition, robotics, object segmentation …
areas of artificial intelligence: pattern recognition, robotics, object segmentation …
Machine learning algorithms and fault detection for improved belief function based decision fusion in wireless sensor networks
Decision fusion is used to fuse classification results and improve the classification accuracy
in order to reduce the consumption of energy and bandwidth demand for data transmission …
in order to reduce the consumption of energy and bandwidth demand for data transmission …
A review of spectrum sensing in modern cognitive radio networks
MU Muzaffar, R Sharqi - Telecommunication Systems, 2024 - Springer
Cognitive radio network (CRN) is a pioneering technology that was developed to improve
efficiency in spectrum utilization. It provides the secondary users with the privilege to …
efficiency in spectrum utilization. It provides the secondary users with the privilege to …
A survey on technological trends to enhance spectrum-efficiency in 6g communications
The research community has already identified that, by 2030, 5G networks will reach the
capacity limits, and, hence, will be inadequate to support next-generation bandwidth-hungry …
capacity limits, and, hence, will be inadequate to support next-generation bandwidth-hungry …