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Deep Reinforcement Learning for Intelligent Reflecting Surface-assisted D2D Communications
In this paper, we propose a deep reinforcement learning (DRL) approach for solving the optimisation problem of the network's sum-rate in device-to-device (D2D) communications supported by an intelligent reflecting surface (IRS).
RIS-assisted UAV Communications for IoT with Wireless Power Transfer Using Deep Reinforcement Learning
We formulate a Markov decision process and propose two deep reinforcement learning algorithms to solve the optimization problem of maximizing the total network sum-rate.
3D UAV Trajectory and Data Collection Optimisation via Deep Reinforcement Learning
Unmanned aerial vehicles (UAVs) are now beginning to be deployed for enhancing the network performance and coverage in wireless communication.
Reconfigurable Intelligent Surface-assisted Multi-UAV Networks: Efficient Resource Allocation with Deep Reinforcement Learning
In this paper, we propose reconfigurable intelligent surface (RIS)-assisted unmanned aerial vehicles (UAVs) networks that can utilise both advantages of UAV's agility and RIS's reflection for enhancing the network's performance.
Cyberattack Detection in Mobile Cloud Computing: A Deep Learning Approach
With the rapid growth of mobile applications and cloud computing, mobile cloud computing has attracted great interest from both academia and industry.
