Spectrum sensing for cognitive radio: Recent advances and future challenge

A Nasser, H Al Haj Hassan, J Abou Chaaya… - Sensors, 2021 - mdpi.com
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 …

Resource allocation trends for ultra dense networks in 5G and beyond networks: A classification and comprehensive survey

N Sharma, K Kumar - Physical Communication, 2021 - Elsevier
With an exaggerating upsurge in mobile data traffic, the wireless networks are confronted
with a subtle task of enhancing their network capacity. The shortage of spectrum resources …

Dynamic SDN-based radio access network slicing with deep reinforcement learning for URLLC and eMBB services

A Filali, Z Mlika, S Cherkaoui… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Radio access network (RAN) slicing is a key technology that enables 5G network to support
heterogeneous requirements of generic services, namely ultra-reliable low-latency …

Secure and energy efficient transmission for IRS-assisted cognitive radio networks

X Wu, J Ma, Z Xing, C Gu, X Xue… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
The spectrum efficiency (SE) and security of the secondary users (SUs) in the cognitive radio
networks (CRNs) have become two main issues due to the limitation interference to the …

Spectrum Evaluation in CR-Based Smart Healthcare Systems Using Optimizable Tree Machine Learning Approach

A Raza, M Ali, MK Ehsan, AH Sodhro - Sensors, 2023 - mdpi.com
The rapid technological advancements in the current modern world bring the attention of
researchers to fast and real-time healthcare and monitoring systems. Smart healthcare is …

Machine learning for spectrum information and routing in multihop green cognitive radio networks

A Paul, SP Maity - IEEE Transactions on Green …, 2021 - ieeexplore.ieee.org
Research works on cognitive radio networks (CRNs) together with energy harvesting (EH)
promise to address the spectrum scarcity and limited battery power problems on the wireless …

When machine learning meets spectrum sharing security: Methodologies and challenges

Q Wang, H Sun, RQ Hu… - IEEE Open Journal of the …, 2022 - ieeexplore.ieee.org
The exponential growth of Internet connected systems has generated numerous challenges,
such as spectrum shortage issues, which require efficient spectrum sharing (SS) solutions …

Deep learning-based joint NOMA signal detection and power allocation in cognitive radio networks

A Kumar, K Kumar - IEEE Transactions on Cognitive …, 2022 - ieeexplore.ieee.org
Presently, Non-Orthogonal Multiple Access (NOMA) frequently uses Successive Interference
Cancellation (SIC) with channel estimation to detect the receivers' signal successfully …

Dynamic channel selection and transmission scheduling for cognitive radio networks

X Zhu, Y Huang, Q Wu, F Zhou, X Ge… - IEEE Internet of Things …, 2022 - ieeexplore.ieee.org
Cognitive radio networks (CRNs) are expected to be promising techniques for improving the
spectrum efficiency of wireless network utility in the squeezed sub-6-GHz frequency bands …

Machine learning empowered green task offloading for mobile edge computing in 5G networks

A Kaur, A Godara - IEEE Transactions on Network and Service …, 2023 - ieeexplore.ieee.org
With the exponential growth of computation-intensive and latency-sensitive applications in
5G, it is hard to satisfy the heterogeneous requirements for increased data traffic with limited …