The fifth generation (5G) of cellular networks aims at providing very high data rates, ultra-
reliable low latency, and massive connection density. As one of the fundamental design …

Multipath transport protocols utilize multiple network paths (eg, WiFi and cellular) to achieve
improved performance and reliability, compared with their single-path counterparts. The …

The Multipath TCP (MPTCP) protocol, featured by its ability of capacity aggregation across
multiple links and connectivity maintenance against single-path failure, has been attracting …

In this paper, we develop a knowledge-assisted deep reinforcement learning (DRL)
algorithm to design wireless schedulers in the fifth-generation (5G) cellular networks with …

The massive growth in mobile data traffic and the heterogeneity and stringency of Quality of
Service (QoS) requirements of various applications have put significant pressure on the …

In this paper, we propose a novel meta-scheduling framework with cooperative learning that
fully exploits a functional split structure of the base station (BS) consisting of a central unit …

Interactive applications have deadline requirements, eg video conferencing and online
gaming. Compared with a single path, which may be less stable or bandwidth insufficient …

Dominated by delay-sensitive and massive data applications, radio resource management
in 5G access networks is expected to satisfy very stringent delay and packet loss …

We present a practical approach of how deep learning models can improve 5G network
service. We demonstrate the potential of a deep Q-network agent applied to a traffic …

Increasing bandwidth demands of mobile video streaming pose a challenge in optimizing
the Quality of Experience (QoE) for better user engagement. Multipath transmission …