This paper proposes a paradigm of uncertainty injection for training deep learning model to
solve robust optimization problems. The majority of existing studies on deep learning focus …

Transmit power control (PC) will become increasingly crucial in alleviating interference as
the densification of the wireless networks continues towards 6G. However, the practicality of …

Optimal resource allocation in modern communication networks calls for the optimization of
objective functions that are only accessible via costly separate evaluations for each …

Relay nodes are used to improve the throughput, delay and reliability performance of energy
harvesting networks by assisting both energy and information transfer between sources and …

Resource management plays a pivotal role in wireless networks, which, unfortunately, leads
to challenging NP-hard problems. Artificial Intelligence (AI), especially deep learning …

This paper optimizes predictive power allocation to minimize the average transmit power for
video streaming subject to the constraint on stalling time, one of the most important factors …

Neural networks have been widely utilized for wireless communication optimizations. In
most of the literature, a dedicated neural network is trained for each specific optimization …

Resource allocation is a fundamental research topic in wireless communications. With the
rapid development of wireless communication systems, the conventional optimization …

In most applications of utilizing neural networks for mathematical optimization, a dedicated
model is trained for each specific optimization objective. However, in many scenarios …

A proposed mechanism for interference management and scheduling links in device‐to‐
device (D2D) networks with full‐duplex relays (FDRs) is FDR‐information theoretic links …