[HTML][HTML] Energy-efficient joint resource allocation in 5G HetNet using multi-agent parameterized deep reinforcement learning
Small cells are a promising technique to improve the capacity and throughput of future
wireless networks. However, user association and power allocation in heterogeneous …
wireless networks. However, user association and power allocation in heterogeneous …
Energy-efficient power allocation and user association in heterogeneous networks with deep reinforcement learning
CK Hsieh, KL Chan, FT Chien - Applied Sciences, 2021 - mdpi.com
This paper studies the problem of joint power allocation and user association in wireless
heterogeneous networks (HetNets) with a deep reinforcement learning (DRL)-based …
heterogeneous networks (HetNets) with a deep reinforcement learning (DRL)-based …
Multi-agent deep reinforcement learning for resource allocation in the multi-objective HetNet
H Nie, S Li, Y Liu - 2021 International Wireless …, 2021 - ieeexplore.ieee.org
Resource allocation in a heterogeneous network is an NP-hard problem, especially in 5G
network scenarios. Multiobjective optimization in resource allocation is a challenging task …
network scenarios. Multiobjective optimization in resource allocation is a challenging task …
Deep reinforcement learning framework for joint resource allocation in heterogeneous networks
Y Zhang, C Kang, YL Teng, S Li… - 2019 IEEE 90th …, 2019 - ieeexplore.ieee.org
In this study, a deep reinforcement learning (DRL) method was employed to solve the joint
optimization problem for user association, resource allocation, and power allocation in …
optimization problem for user association, resource allocation, and power allocation in …
A survey on applications of deep reinforcement learning in resource management for 5G heterogeneous networks
YL Lee, D Qin - 2019 Asia-Pacific Signal and Information …, 2019 - ieeexplore.ieee.org
Heterogeneous networks (HetNets) have been regarded as the key technology for fifth
generation (5G) communications to support the explosive growth of mobile traffics. By …
generation (5G) communications to support the explosive growth of mobile traffics. By …
Hierarchical multi-agent DRL-based framework for joint multi-RAT assignment and dynamic resource allocation in next-generation hetnets
This article considers the problem of cost-aware downlink sum-rate maximization via joint
optimal radio access technologies (RATs) assignment and power allocation in next …
optimal radio access technologies (RATs) assignment and power allocation in next …
A deep reinforcement learning for user association and power control in heterogeneous networks
Heterogeneous network (HetNet) is a promising solution to satisfy the unprecedented
demand for higher data rate in the next generation mobile networks. Different from the …
demand for higher data rate in the next generation mobile networks. Different from the …
Deep reinforcement learning for user association and resource allocation in heterogeneous networks
Heterogeneous networks (HetNets) can offload the traffic and reduce the deployment cost,
which is regarded as a promising technique in next-generation cellular networks. Because …
which is regarded as a promising technique in next-generation cellular networks. Because …
DeepRAT: A DRL-based framework for multi-RAT assignment and power allocation in HetNets
Wireless heterogeneous networks (HetNets), where several systems with multi-radio access
technologies (multi-RATs) coexist for massive multi-connectivity networks, are in service …
technologies (multi-RATs) coexist for massive multi-connectivity networks, are in service …
DRL-Based joint RAT association, power and bandwidth optimization for future HetNets
Multi-radio access technologies (RATs) networks, where various heterogeneous networks
(HetNets) coexist, are in service nowadays and considered a main enabling technology for …
(HetNets) coexist, are in service nowadays and considered a main enabling technology for …
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