Spectrum sensing based on deep learning classification for cognitive radios
S Zheng, S Chen, P Qi, H Zhou… - China …, 2020 - ieeexplore.ieee.org
Spectrum sensing is a key technology for cognitive radios. We present spectrum sensing as
a classification problem and propose a sensing method based on deep learning …
a classification problem and propose a sensing method based on deep learning …
A review of spectrum sensing in modern cognitive radio networks
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 …
Hybrid machine-learning-based spectrum sensing and allocation with adaptive congestion-aware modeling in CR-assisted IoV networks
Unlicensed cognitive-radio (CR)-assisted Internet of Vehicles (IoV) users can access
licensed providers' radio spectrum and concurrently utilize the dedicated channel for data …
licensed providers' radio spectrum and concurrently utilize the dedicated channel for data …
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 …
Cooperative spectrum sensing in cognitive radio networks using machine learning techniques
RG Nair, K Narayanan - Applied Nanoscience, 2023 - Springer
For effective utilization of the available spectrum and for preventing the channel interference
among the users the sensing of the availability of spectrum becomes an essential task in …
among the users the sensing of the availability of spectrum becomes an essential task in …
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 …
Limited data spectrum sensing based on semi-supervised deep neural network
Y Zhang, Z Zhao - IEEE Access, 2021 - ieeexplore.ieee.org
Spectrum sensing methods based on deep learning require massive amounts of labeled
samples. To address the scarcity of labeled samples in a real radio environment, this paper …
samples. To address the scarcity of labeled samples in a real radio environment, this paper …
Soft decision cooperative spectrum sensing with entropy weight method for cognitive radio sensor networks
H Lin, L Du, Y Liu - IEEE Access, 2020 - ieeexplore.ieee.org
By fully utilizing the spatial gain and exploiting the multiuser diversity, cooperative spectrum
sensing can enhance the sensing accuracy. In the actual wireless environment, the effect of …
sensing can enhance the sensing accuracy. In the actual wireless environment, the effect of …
[HTML][HTML] Kernel fuzzy c-means clustering on energy detection based cooperative spectrum sensing
Cooperation in spectral sensing (SS) offers a fast and reliable detection of primary user (PU)
transmission over a frequency spectrum at the expense of increased energy consumption …
transmission over a frequency spectrum at the expense of increased energy consumption …
Primary user adversarial attacks on deep learning-based spectrum sensing and the defense method
S Zheng, L Ye, X Wang, J Chen, H Zhou… - China …, 2021 - ieeexplore.ieee.org
The spectrum sensing model based on deep learning has achieved satisfying detection
performence, but its robustness has not been verified. In this paper, we propose primary …
performence, but its robustness has not been verified. In this paper, we propose primary …