In the coming 6G communications, network densification, high throughput, positioning
accuracy, energy efficiency, and many other key performance indicator requirements are …

As a key technique for enabling artificial intelligence, machine learning (ML) is capable of
solving complex problems without explicit programming. Motivated by its successful …

Deploying small cell base stations (SBS) under the coverage area of a macro base station
(MBS), and caching popular contents at the SBSs in advance, are effective means to provide …

The integration of communications with different scales, diverse radio access technologies,
and various network resources renders next-generation wireless networks (NGWNs) highly …

This paper studies the joint communication, caching and computing design problem for
achieving the operational excellence and the cost efficiency of the vehicular networks …

Edge networking is a complex and dynamic computing paradigm that aims to push cloud re-
sources closer to the end user improving responsiveness and reducing backhaul traffic …

Mobile data traffic is currently growing exponentially and these rapid increases have caused
the backhaul data rate requirements to become the major bottleneck to reducing costs and …

Small basestations (SBs) equipped with caching units have potential to handle the
unprecedented demand growth in heterogeneous networks. Through low-rate, backhaul …

With outstanding features, machine learning (ML) has become the backbone of numerous
applications in wireless networks. However, the conventional ML approaches face many …

With emergence of Internet of Things (IoT), wireless traffic has grown dramatically, posing
severe strain on core network and backhaul bandwidth. Proactive caching in mobile edge …