… heterogeneous communication characteristics have motivated several recent studies on
federated learning for wireless networks (… Heterogeneity: Wireless devices exhibit heterogeneity …

… To achieve this goal, machine learning (especially deep learning) has become a … wireless
networks (eg, WiFi networks) [30]. Even though some interests in the IoT and machine learning …

… are discussed with regard to machine learning based network … the popular machine learning
techniques utilized in wireless networks, … The applications of machine learning in resource …

… In this paper, we study the user association problem from a deep learning perspective.
We propose a U-Net based deep learning scheme aimed at intelligently associating user …

… In this article, we will introduce the basic concept of machine learning algorithms and the …
supervised, unsupervised, and reinforcement learning. Machine learning can be widely used in …

… cellular networks that facilitate important network-level decision-making. They have gained
a lot of attention from researchers working in the field of machine learning … machine learning …

… Heterogeneous Wireless Networks We consider time-slotted heterogeneous wireless networks
… packets to an access point (AP) via a shared wireless channel, as illustrated in Fig. 2. We …

… generation (5G) wireless network. The 6G network structure is envisioned to be extremely
… Mobile networks have already created a large data source to efficiently manage HetNets by …

… mainly focuses on deep reinforcement learning for RRAM in wireless networks, we included
… ”AND/OR” combinations of them; ”deep reinforcement learning,” ”DRL,” ”resource allocation,…

… deep reinforcement learning for intelligent resource management in intelligent wireless
networks in … the effectiveness and advance of machine learning in intelligent wireless networks. …