… as userassociation and resource allocation (UARA). The problem of userassociation was … Here, reinforcement learning approach is applied to solve the joint optimization problem of …
… in the userassociation problem for AmBC-based SRN. The base station (BS) in the primary network serves the cellular users … In this paper, we consider the userassociation policy is …
H Ding, F Zhao, J Tian, D Li, H Zhang - Ad Hoc Networks, 2020 - Elsevier
… analysis, as deepreinforcement learning shows great potential in handling large systems, in this paper, a multi-agent deepreinforcement learning for joint userassociation and power …
Z Li, M Chen, K Wang, C Pan… - 2020 IEEE International …, 2020 - ieeexplore.ieee.org
… an online deepreinforcement learning (DRL) … deep neural networks (DNNs) can generate userassociation solutions. We use a shared memory structure to store the best association …
CK Hsieh, KL Chan, FT Chien - Applied Sciences, 2021 - mdpi.com
… and applying traditional deepreinforcement approaches such as deep Q learning, we propose working on the hybrid space directly by using the novel parameterized deep Q-network (P…
… on multi-agent reinforcement learning (MARL) for userassociation in heterogeneous network [8]. … , we propose a distributed deep MARL framework for userassociation to maximize the …
… userassociation between a TBS and a HAPS in a wireless multi-input multi-output (MIMO) network to maximize users’ … an optimization-based userassociation method. We look at the …
THL Dinh, M Kaneko, K Wakao… - 2021 IEEE 18th …, 2021 - ieeexplore.ieee.org
… to make use of a DeepReinforcement Learning (DRL) technique based on Deep QNetworks (DQN) in order to solve this challenging problem. Namely, the mobile users autonomously …
J Moon, S Kim, H Ju, B Shim - IEEE Transactions on Green …, 2023 - ieeexplore.ieee.org
… a decentralized mechanism for the userassociation?” … userassociation technique based on deepreinforcement learning (DRL). While most of the conventional userassociation …