It has been a long-held belief that judicious resource allocation is critical to mitigating
interference, improving network efficiency, and ultimately optimizing wireless communication …

Deep neural networks have recently emerged as a disruptive technology to solve NP-hard
wireless resource allocation problems in a real-time manner. However, the adopted neural …

Resource allocation in wireless networks, such as device-to-device (D2D) communications,
is usually formulated as mixed integer nonlinear programming (MINLP) problems, which are …

This paper introduces a combined calibrated learning and bandit approach to online
distributed power control in small cell networks operated under the same frequency …

Resource allocation for device-to-device (D2D) communications is usually formulated as
mixed integer nonlinear programming (MINLP) problems, which are generally NP-hard and …

In this paper, we present a learning-based approach for solving shuffled linear systems in
header-free communication, thereby supporting low-latency communication. The resulting …