… the state of UAV-enabled wireless network and for carrying out actions … learning rate is
leveraged in the proposed D-DQN based algorithm for attaining a tradeoff between accelerating …

… Furthermore, the assumption of ideal cooperation among the nodes can be challenging in
practical wireless networks, where any coordination among wireless nodes are usually limited …

… Section II outlines the power control problem in the wireless cellular network with IBC. In
Section III, the top-level DRL design for a static optimization problem is introduced and analyzed…

… Deep learning improves the performance when the model-based methods fail. Finally, …
learning applies to wireless communication security. In this context, adversarial machine learning …

… Access Network (RAN) slicing baselines. Finally, we propose a transfer learningaccelerated
DRL-… Such challenges are rarely tackled in the wireless networks literature or research. On a …

… applied to the MINLP problems in other wireless networks. … imitation learning, to solve the
MINLP problems by accelerating … cloud radio access networks (CloudRANs). Our key idea is to …

… To ensure that the system can quickly adapt to the dynamics of a practical wireless environment,
we have exploited a TDerror-based prioritization that accelerates the learning process. …

… In this study, our focus is on designing an FPGA accelerator for ESN-based symbol detection
within a real-time MIMOOFDM system, facing challenges from a more complicated wireless …

… learning algorithms for in-network processing of graph-valued data. A generic learning problem
… An efficient accelerated proximal gradient algorithm with quantifiable iteration complexity …

… In [9], the authors propose a deep reinforcement learning … caching enabled fog radio access
networks. Note that, both [8] … learning-based coded caching strategy in a wireless network …