This paper presents a comprehensive literature review on applications of deep
reinforcement learning (DRL) in communications and networking. Modern networks, eg …

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

To process and transfer large amounts of data in emerging wireless services, it has become
increasingly appealing to exploit distributed data communication and learning. Specifically …

Unmanned aerial vehicles (UAVs) can help small-cell base stations (SBSs) offload traffic via
wireless backhaul to improve coverage and increase rate. However, the capacity of …

Both caching and interference alignment (IA) are promising techniques for next-generation
wireless networks. Nevertheless, most of the existing works on cache-enabled IA wireless …

Mobile data traffic grew by 74% in 2015 and it is expected to grow eight-fold by 2020. Future
wireless networks will need to deploy massive number of small cells to cope with this …

Building on the recent coded-caching breakthrough by Maddah-Ali and Niesen, the work
here considers the K-user cache-aided wireless multi-antenna symmetric broadcast channel …

In future generation mobile systems, hyperdense small cell networks will be deployed to
meet the tremendous growth of mobile traffic, in which interference is a key limitation …

Edge caching, which offers application versatility and a range of benefits, has exerted a
significant impact on the adoption and development of fifth-generation networks and …

Both caching and interference alignment (IA) are promising techniques for future wireless
networks. Nevertheless, most of existing works on cache-enabled IA wireless networks …