Search Results for author: Helin Yang

Found 5 papers, 0 papers with code

Deep Reinforcement Learning Based Multidimensional Resource Management for Energy Harvesting Cognitive NOMA Communications

no code implementations17 Sep 2021 Zhaoyuan Shi, Xianzhong Xie, Huabing Lu, Helin Yang, Jun Cai, Zhiguo Ding

Due to the non-convexity of this optimization problem and the stochastic nature of the wireless environment, we propose a distributed multidimensional resource management algorithm based on deep reinforcement learning (DRL).


Intelligent Reflecting Surface Assisted Anti-Jamming Communications Based on Reinforcement Learning

no code implementations23 Dec 2020 Helin Yang, Zehui Xiong, Jun Zhao, Dusit Niyato, Qingqing Wu, Massimo Tornatore, Stefano Secci

Aiming to enhance the communication performance against smart jammer, an optimization problem for jointly optimizing power allocation at the base station (BS) and reflecting beamforming at the IRS is formulated.


Advanced NOMA Assisted Semi-Grant-Free Transmission Schemes for Randomly Distributed Users

no code implementations17 Dec 2020 Huabing Lu, Xianzhong Xie, Zhaoyuan Shi, Hongjiang Lei, Helin Yang, Jun Cai

Non-orthogonal multiple access (NOMA) assisted semi-grant-free (SGF) transmission has recently received significant research attention due to its outstanding ability of serving grant-free (GF) users with grant-based (GB) users' spectrum, which greatly improves the spectrum efficiency and effectively relieves the massive access problem of 5G and beyond networks.

Information Theory Information Theory

Privacy-Preserving Federated Learning for UAV-Enabled Networks: Learning-Based Joint Scheduling and Resource Management

no code implementations28 Nov 2020 Helin Yang, Jun Zhao, Zehui Xiong, Kwok-Yan Lam, Sumei Sun, Liang Xiao

However, due to the privacy concerns of devices and limited computation or communication resource of UAVs, it is impractical to send raw data of devices to UAV servers for model training.

Distributed Computing Federated Learning

Deep Reinforcement Learning Based Intelligent Reflecting Surface for Secure Wireless Communications

no code implementations27 Feb 2020 Helin Yang, Zehui Xiong, Jun Zhao, Dusit Niyato, Liang Xiao, Qingqing Wu

As the system is highly dynamic and complex, and it is challenging to address the non-convex optimization problem, a novel deep reinforcement learning (DRL)-based secure beamforming approach is firstly proposed to achieve the optimal beamforming policy against eavesdroppers in dynamic environments.


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