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 …
Review on classical to deep spectrum sensing in cognitive radio networks
GK Shekhawat, RP Yadav - 2021 Sixth International …, 2021 - ieeexplore.ieee.org
Cognitive Radio (CR), a promising next-generation wireless network has been progressing
well that deals with the scant radio spectrum issues using a dynamic spectrum access …
well that deals with the scant radio spectrum issues using a dynamic spectrum access …
Deep residual learning-based cognitive model for detection and classification of transmitted signal patterns in 5G smart city networks
Primary user (PU) signal detection or classification is a critical component of cognitive radio
(CR) related wireless communication applications. In CR, the PU detection methods are …
(CR) related wireless communication applications. In CR, the PU detection methods are …
A usage aware dynamic spectrum access scheme for interweave cognitive radio network by exploiting deep reinforcement learning
Future-generation wireless networks should accommodate surging growth in mobile data
traffic and support an increasingly high density of wireless devices. Consequently, as the …
traffic and support an increasingly high density of wireless devices. Consequently, as the …
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 …
Deep reinforcement learning-based distributed dynamic spectrum access in multi-user multi-channel cognitive radio internet of things networks
X Zhang, Z Chen, Y Zhang, Y Liu… - IEEE Internet of Things …, 2024 - ieeexplore.ieee.org
Integrating cognitive radio into Internet of Things (IoT) is conducive to reducing spectrum
scarcity for large-scale IoT deployment, where a core technology is the design of spectrum …
scarcity for large-scale IoT deployment, where a core technology is the design of spectrum …
A cooperative spectrum sensing with multi-agent reinforcement learning approach in cognitive radio networks
Cognitive radio networks (CRNs) can greatly improve the temporal and spatial spectrum
utilization by identifying and exploring spectrum holes of the licensed primary users (PUs) …
utilization by identifying and exploring spectrum holes of the licensed primary users (PUs) …
Deep learning-based selective spectrum sensing and allocation in cognitive vehicular radio networks
The main challenge with Vehicular Ad-Hoc Networks (VANETs) for assisting Intelligent
Transportation Services (ITSs) is ensuring effective data delivery under various network …
Transportation Services (ITSs) is ensuring effective data delivery under various network …
Pu-detnet: Deep unfolding aided smart sensing framework for cognitive radio
Spectrum sensing in cognitive radio (CR) paradigm can be broadly categorized as analytical-
based and data-driven approaches. The former is sensitive to model inaccuracies in …
based and data-driven approaches. The former is sensitive to model inaccuracies in …
Dynamic spectrum access for internet-of-things based on federated deep reinforcement learning
The explosive growth of Internet-of-Things (IoT) applications such as smart cities and
Industry 4.0 have led to drastic increase in demand for wireless bandwidth, hence motivating …
Industry 4.0 have led to drastic increase in demand for wireless bandwidth, hence motivating …
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