B Yang, X Cao, Z Han, L Qian - IEEE Transactions on Wireless …, 2019 - ieeexplore.ieee.org
… To achieve this goal, machinelearning (especially deeplearning) has become a … wireless networks (eg, WiFinetworks) [30]. Even though some interests in the IoT and machinelearning …
Y Sun, M Peng, Y Zhou, Y Huang… - … Surveys & Tutorials, 2019 - ieeexplore.ieee.org
… are discussed with regard to machinelearning based network … the popular machinelearning techniques utilized in wirelessnetworks, … The applications of machinelearning in resource …
Y Zhang, L Xiong, J Yu - IEEE Access, 2020 - ieeexplore.ieee.org
… In this paper, we study the user association problem from a deeplearning perspective. We propose a U-Net based deeplearning scheme aimed at intelligently associating user …
… In this article, we will introduce the basic concept of machinelearning algorithms and the … supervised, unsupervised, and reinforcementlearning. Machinelearning can be widely used in …
… cellularnetworks that facilitate important network-level decision-making. They have gained a lot of attention from researchers working in the field of machinelearning … machinelearning …
Y Yu, T Wang, SC Liew - IEEE journal on selected areas in …, 2019 - ieeexplore.ieee.org
… HeterogeneousWirelessNetworks We consider time-slotted heterogeneouswirelessnetworks … packets to an access point (AP) via a shared wireless channel, as illustrated in Fig. 2. We …
… generation (5G) wirelessnetwork. The 6G network structure is envisioned to be extremely … Mobilenetworks have already created a large data source to efficiently manage HetNets by …
… mainly focuses on deepreinforcementlearning for RRAM in wirelessnetworks, we included … ”AND/OR” combinations of them; ”deepreinforcementlearning,” ”DRL,” ”resource allocation,…
H Yang, X Xie, M Kadoch - IEEE Network, 2020 - ieeexplore.ieee.org
… deepreinforcementlearning for intelligent resource management in intelligent wireless networks in … the effectiveness and advance of machinelearning in intelligent wireless networks. …