Wireless networks are a key component of the telecommunications infrastructure in our
society, and wireless services become increasingly important as the applications of wireless …

Machine learning (ML) provides effective means to learn from spectrum data and solve
complex tasks involved in wireless communications. Supported by recent advances in …

Motivated by the advancing computational capacity of distributed end-user equipment (UE),
as well as the increasing concerns about sharing private data, there has been considerable …

Machine learning provides automated means to capture complex dynamics of wireless
spectrum and support better understanding of spectrum resources and their efficient …

In this article, we investigate intelligent anti-jamming communication method for wireless
sensor networks. The stochastic game framework is introduced to model and analyze the …

Deep learning provides powerful means to learn from spectrum data and solve complex
tasks in 5G and beyond such as beam selection for initial access (IA) in mmWave …

In this paper, reinforcement learning (RL) for network slicing is considered in NextG radio
access networks, where the base station (gNodeB) allocates resource blocks (RBs) to the …

As the applications of deep reinforcement learning (DRL) in wireless communication grow,
sensitivity of DRL based wireless communication strategies against adversarial attacks has …

Channel hopping provides a defense mechanism against jamming attacks in large scale
Internet of Things (IoT) networks. However, a sufficiently powerful attacker may be able to …

In this paper, reinforcement learning (RL) for network slicing is considered in next
generation (NextG) radio access networks, where the base station (gNodeB) allocates …