14 citations · 24 across the 4 of their papers we have counts for
7 papers
Deep Reinforcement Learning Based Multidimensional Resource Management for Energy Harvesting Cognitive NOMA Communications
Zhaoyuan Shi, Xianzhong Xie, Huabing Lu +3
The combination of energy harvesting (EH), cognitive radio (CR), and non-orthogonal multiple access (NOMA) is a promising solution to improve energy efficiency and spectral efficie…
Intelligent Reflecting Surface Assisted Anti-Jamming Communications Based on Reinforcement Learning
Helin Yang, Zehui Xiong, Jun Zhao +4
Malicious jamming launched by smart jammer, which attacks legitimate transmissions has been regarded as one of the critical security challenges in wireless communications. Thus, th…
Privacy-Preserving Federated Learning for UAV-Enabled Networks: Learning-Based Joint Scheduling and Resource Management
Helin Yang, Jun Zhao, Zehui Xiong +3
Unmanned aerial vehicles (UAVs) are capable of serving as flying base stations (BSs) for supporting data collection, artificial intelligence (AI) model training, and wireless commu…
Intelligent Reflecting Surface Assisted Anti-Jamming Communications: A Fast Reinforcement Learning Approach
Helin Yang, Zehui Xiong, Jun Zhao +4
Malicious jamming launched by smart jammers can attack legitimate transmissions, which has been regarded as one of the critical security challenges in wireless communications. With…
Deep Reinforcement Learning Based Intelligent Reflecting Surface for Secure Wireless Communications
Helin Yang, Zehui Xiong, Jun Zhao +3
In this paper, we study an intelligent reflecting surface (IRS)-aided wireless secure communication system for physical layer security, where an IRS is deployed to adjust its surfa…
Deep Reinforcement Learning Based Massive Access Management for Ultra-Reliable Low-Latency Communications
Helin Yang, Zehui Xiong, Jun Zhao +3
With the rapid deployment of the Internet of Things (IoT), fifth-generation (5G) and beyond 5G networks are required to support massive access of a huge number of devices over limi…