Model-free learning of optimal deterministic resource allocations in wireless systems via action-space exploration
H Hashmi, DS Kalogerias - 2021 IEEE 31st International …, 2021 - ieeexplore.ieee.org
Wireless systems resource allocation refers to perpetual and challenging nonconvex
constrained optimization tasks, which are especially timely in modern communications and …
constrained optimization tasks, which are especially timely in modern communications and …
A zeroth-order learning algorithm for ergodic optimization of wireless systems with no models and no gradients
Optimal resource allocation in real-world wireless systems is rather challenging, not only
due to the unavailability of accurate statistical channel models, but also because …
due to the unavailability of accurate statistical channel models, but also because …
Model-free learning of optimal ergodic policies in wireless systems
Learning optimal resource allocation policies in wireless systems can be effectively
achieved by formulating finite dimensional constrained programs which depend on system …
achieved by formulating finite dimensional constrained programs which depend on system …
Learning constrained resource allocation policies in wireless control systems
Emerging applications in IoT systems employ wireless communication networks to
exchange data between spatially distributed components of a control system. As wireless …
exchange data between spatially distributed components of a control system. As wireless …
Dual domain learning of optimal resource allocations in wireless systems
We consider the problem of finding optimal resource allocations subject to system
constraints in a generic class of problems in wireless communications. These problems are …
constraints in a generic class of problems in wireless communications. These problems are …
Resource allocation in wireless control systems via deep policy gradient
In wireless control systems, remote control of plants is achieved through closing of the
control loop over a wireless channel. As wireless communication is noisy and subject to …
control loop over a wireless channel. As wireless communication is noisy and subject to …
Deep neural networks with data rate model: Learning power allocation efficiently
J Guo, C Yang - IEEE Transactions on Communications, 2023 - ieeexplore.ieee.org
Learning-based resource allocation can be implemented in real-time, but deep neural
networks (DNNs) developed in other fields such as computer vision are with high training …
networks (DNNs) developed in other fields such as computer vision are with high training …
A State-Augmented Approach for Learning Optimal Resource Management Decisions in Wireless Networks
We consider a radio resource management (RRM) problem in a multi-user wireless network,
where the goal is to optimize a network-wide utility function subject to constraints on the …
where the goal is to optimize a network-wide utility function subject to constraints on the …
A Partially Observable Deep Multi-Agent Active Inference Framework for Resource Allocation in 6G and Beyond Wireless Communications Networks
Resource allocation is of crucial importance in wireless communications. However, it is
extremely challenging to design efficient resource allocation schemes for future wireless …
extremely challenging to design efficient resource allocation schemes for future wireless …
Learning resource scheduling with high priority users using deep deterministic policy gradients
S Gracla, E Beck, C Bockelmann… - ICC 2022-IEEE …, 2022 - ieeexplore.ieee.org
Advances in mobile communication capabilities open the door for closer integration of pre-
hospital and in-hospital care processes. For example, medical specialists can be enabled to …
hospital and in-hospital care processes. For example, medical specialists can be enabled to …