The frontiers of deep reinforcement learning for resource management in future wireless HetNets: Techniques, challenges, and research directions
… In this context, emerging Deep Reinforcement Learning (DRL) techniques are expected to
… the RRAM in future wireless HetNets. In this paper, we conduct a systematic in-depth, and …
… the RRAM in future wireless HetNets. In this paper, we conduct a systematic in-depth, and …
Deep reinforcement learning for radio resource allocation and management in next generation heterogeneous wireless networks: A survey
… In this context, emerging Deep Reinforcement Learning (DRL) techniques are expected to
… the RRAM in future wireless HetNets. In this paper, we conduct a systematic in-depth, and …
… the RRAM in future wireless HetNets. In this paper, we conduct a systematic in-depth, and …
Deep reinforcement learning for dynamic uplink/downlink resource allocation in high mobility 5G HetNet
… for constructing the wireless heterogeneous network (HetNet). To … and proposed a novel
deep reinforcement learning based … In the proposal, the deep neural network is employed to …
deep reinforcement learning based … In the proposal, the deep neural network is employed to …
SecBoost: Secrecy-aware deep reinforcement learning based energy-efficient scheme for 5G HetNets
… of HetNet is expected to be around $51.1 billion by the end of 2027 [3]. However, despite the
promising gains of HetNets in 5G, the vast number of devices and wireless … Also, HetNet is …
promising gains of HetNets in 5G, the vast number of devices and wireless … Also, HetNet is …
Deep reinforcement learning based dynamic multichannel access in HetNets
… HetNet Model Consider a downlink dynamic HetNet based on LWA using the wireless
fidelity (WiFi) for traffic offloading, wherein a base station (BS) and K WiFi access points (WAPs) …
fidelity (WiFi) for traffic offloading, wherein a base station (BS) and K WiFi access points (WAPs) …
A power allocation scheme based on deep reinforcement learning in HetNets
Q Su, B Li, C Wang, C Qin… - … international conference on …, 2020 - ieeexplore.ieee.org
… Deep reinforcement learning (DQN) is the solution to the … and deep learning are integrated
into wireless communication … construct the self-organized HetNet to handle huge states space …
into wireless communication … construct the self-organized HetNet to handle huge states space …
An overview of intelligent wireless communications using deep reinforcement learning
… to address emerging issues in wireless communications. These issues include … HetNets.
Finally, critical challenges and future research directions of applying DRL in intelligent wireless …
Finally, critical challenges and future research directions of applying DRL in intelligent wireless …
[HTML][HTML] Energy-efficient joint resource allocation in 5G HetNet using Multi-Agent Parameterized Deep Reinforcement learning
… environment of wireless networks, reinforcement learning (RL… the case of a dense wireless
network with diverse users and … allocation) by utilizing deep reinforcement learning (DRL) in a …
network with diverse users and … allocation) by utilizing deep reinforcement learning (DRL) in a …
Deep reinforcement learning based handoff algorithm in end-to-end network slicing enabling HetNets
F Yang, W Wu, X Wang, Y Zhang… - 2021 IEEE Wireless …, 2021 - ieeexplore.ieee.org
… wireless networks to support different services in vertical industries. In a heterogeneous cellular
network (HetNets… The deep reinforcement learning (DRL) is adopted as the solution, and …
network (HetNets… The deep reinforcement learning (DRL) is adopted as the solution, and …
DeepRAT: A DRL-based framework for multi-RAT assignment and power allocation in HetNets
… technology in the future wireless networks. The extensive … -cooperative multiagent deep
reinforcement learning (DRL)-… We consider a simplified multi-RAT wireless HetNet similar …
reinforcement learning (DRL)-… We consider a simplified multi-RAT wireless HetNet similar …
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