This article proposes a novel multiagent deep reinforcement learning-based algorithm which
can realize federated learning (FL) computation with Internet-of-Underwater-Things (IoUT) …

This paper addresses the problem of radio access technology (RAT) selection in
heterogeneous networks (HetNets). Current approaches rely on signal related metrics such …

This work introduces an innovative Access Point (AP) allocation algorithm for dense Wi-Fi
networks, which relies on a centralised potential game developed in a Software-Defined …

Millimeter-wave (mmWave) base station can offer abundant high capacity channel
resources toward connected vehicles so that quality-of-service (QoS) of them in terms of …

In a cloud radio access network (C-RAN), distributed remote radio heads (RRHs) are
coordinated by baseband units (BBUs) in the cloud. The centralization of signal processing …

Cloud-based Radio Access Network (C-RAN) is a promising architecture for future cellular
networks, in which Baseband Units (BBUs) are placed at a centralized location, with …

This paper presents a novel Access Point (AP) selection strategy based on a potential game
played at a centralized controller. The proposed approach relies on Software Defined …

Cooperative multipoint transmission (CoMP) is one of the most promising paradigms for
mitigating interference in cloud radio access networks (C-RAN). It allows multiple remote …

This paper addresses the problem of Access Point (AP) selection in large scale IEEE 802.11
Wireless Local Area Networks (WLANs) through the study of a shopping mall use-case. We …

摘要无线共享网络的接入资源分散, 容量有限, 且价格互有差异, 为了在保证用户满意度的同时
提高运营商总体收益, 需要对网络接入资源进行合理分配. 因此, 提出了一个基于博弈论的WiFi …