Comprehensive survey of machine learning approaches in cognitive radio-based vehicular ad hoc networks
Nowadays, machine learning (ML), which is one of the most rapidly growing technical tools,
is extensively used to solve critical challenges in various domains. Vehicular ad hoc network …
is extensively used to solve critical challenges in various domains. Vehicular ad hoc network …
Machine learning for 5G/B5G mobile and wireless communications: Potential, limitations, and future directions
ME Morocho-Cayamcela, H Lee, W Lim - IEEE access, 2019 - ieeexplore.ieee.org
Driven by the demand to accommodate today's growing mobile traffic, 5G is designed to be
a key enabler and a leading infrastructure provider in the information and communication …
a key enabler and a leading infrastructure provider in the information and communication …
A survey on deep learning for ultra-reliable and low-latency communications challenges on 6G wireless systems
The sixth generation (6G) wireless communication network presents itself as a promising
technique that can be utilized to provide a fully data-driven network evaluating and …
technique that can be utilized to provide a fully data-driven network evaluating and …
A deep reinforcement learning framework for contention-based spectrum sharing
The increasing number of wireless devices operating in unlicensed spectrum motivates the
development of intelligent adaptive approaches to spectrum access. We consider …
development of intelligent adaptive approaches to spectrum access. We consider …
Breaking wireless propagation environmental uncertainty with deep learning
ME Morocho-Cayamcela, M Maier… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Wireless propagation loss modeling has gained significant attention due to its critical
importance in forthcoming dynamic wireless technologies. Stochastic and map-based …
importance in forthcoming dynamic wireless technologies. Stochastic and map-based …
A Cost-effective RISs Deployment to abate the Coverage Problem in B5G Networks
G Encinas-Lago, A Albanese… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
As upcoming, beyond-5G (B5G) wireless network generations are expected to deliver much
better performance than existing solutions, Reconfigurable intelligent surfaces (RISs) are …
better performance than existing solutions, Reconfigurable intelligent surfaces (RISs) are …
Resource allocation in spectrum access system using multi-objective optimization methods
The paradigm of dynamic shared access aims to provide flexible spectrum usage. Recently,
Federal Communications Commission (FCC) has proposed a new dynamic spectrum …
Federal Communications Commission (FCC) has proposed a new dynamic spectrum …
Dynamic multichannel sensing in cognitive radio: Hierarchical reinforcement learning
S Liu, J Wu, J He - IEEE Access, 2021 - ieeexplore.ieee.org
Efficient use of spectral resources is critical in wireless networks and has been extensively
studied in recent years. Dynamic spectrum access (DSA) is one of the key techniques on …
studied in recent years. Dynamic spectrum access (DSA) is one of the key techniques on …
Analysis of the on-demand spectrum access architecture for CBRS cognitive radio networks
An on-demand spectrum access cognitive radio network offers spectrum services to users,
so that users can dynamically set up application-oriented virtual topologies to support user …
so that users can dynamically set up application-oriented virtual topologies to support user …
A Hierarchical Deep Learning Approach for Optimizing CCA Threshold and Transmit Power in Wi-Fi Networks
The nodes, eg, access points and clients, in current WiFi networks rely on carrier sense
multiple access (CSMA) for channel access. This means they rely on a clear channel …
multiple access (CSMA) for channel access. This means they rely on a clear channel …