A tutorial on ultrareliable and low-latency communications in 6G: Integrating domain knowledge into deep learning

C She, C Sun, Z Gu, Y Li, C Yang… - Proceedings of the …, 2021 - ieeexplore.ieee.org
As one of the key communication scenarios in the fifth-generation and also the sixth-
generation (6G) mobile communication networks, ultrareliable and low-latency …

[HTML][HTML] Wireless control: Retrospective and open vistas

M Pezzutto, S Dey, E Garone, K Gatsis… - Annual Reviews in …, 2024 - Elsevier
The convergence of wireless networks and control engineering has been a technological
driver since the beginning of this century. It has significantly contributed to a wide set of …

Federated learning based resource allocation for wireless communication networks

P Behmandpoor, P Patrinos… - 2022 30th European …, 2022 - ieeexplore.ieee.org
In this paper we introduce federated learning (FL) based resource allocation (RA) for
wireless communication networks, where users cooperatively train a RA policy in a …

Zeroth-order deterministic policy gradient

H Kumar, DS Kalogerias, GJ Pappas… - arXiv preprint arXiv …, 2020 - arxiv.org
Deterministic Policy Gradient (DPG) removes a level of randomness from standard
randomized-action Policy Gradient (PG), and demonstrates substantial empirical success for …

Zeroth-order asynchronous learning with bounded delays with a use-case in resource allocation in communication networks

P Behmandpoor, M Moonen, P Patrinos - arXiv preprint arXiv:2311.04604, 2023 - arxiv.org
Distributed optimization has experienced a significant surge in interest due to its wide-
ranging applications in distributed learning and adaptation. While various scenarios, such …

Model-free decentralized training for deep learning based resource allocation in communication networks

P Behmandpoor, P Patrinos… - 2023 31st European …, 2023 - ieeexplore.ieee.org
Decentralized deep learning (DL) based resource allocation (RA) in communication
networks guarantees scalability and higher communication bandwidth efficiency compared …

Robust and Reliable Stochastic Resource Allocation via Tail Waterfilling

G Yaylali, D Kalogerias - 2023 IEEE 24th International …, 2023 - ieeexplore.ieee.org
Stochastic allocation of resources in the context of wireless systems ultimately demands
reactive decision making for meaningfully optimizing network-wide random utilities, while …

Learning constrained network slicing policies for industrial applications

P Agostini, E Tohidi, M Kasparick… - 2022 IEEE International …, 2022 - ieeexplore.ieee.org
The proliferation of private 5G campus networks into industrial domains has increased the
need for network solutions capable of simultaneously meeting a wide range of technical …

Learning-based resource allocation with dynamic data rate constraints

P Behmandpoor, P Patrinos… - ICASSP 2022-2022 IEEE …, 2022 - ieeexplore.ieee.org
In this paper, we address the problem of resource allocation (RA) in wireless communication
networks, where each user has a dynamic data rate constraint. The objective of RA is to …

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 …