93 citations · 132 across the 6 of their papers we have counts for
6 papers
Deep Reinforcement Learning for Distributed and Uncoordinated Cognitive Radios Resource Allocation
Ankita Tondwalkar, Andres Kwasinski
This paper presents a novel deep reinforcement learning-based resource allocation technique for the multi-agent environment presented by a cognitive radio network where the interac…
Deep Reinforcement Learning for Distributed Uncoordinated Cognitive Radios Resource Allocation
Ankita Tondwalkar, Dr Andres Kwasinski
This paper presents a novel deep reinforcement learning-based resource allocation technique for the multi-agent environment presented by a cognitive radio network that coexists thr…
Neural Network Cognitive Engine for Autonomous and Distributed Underlay Dynamic Spectrum Access
Fatemeh Shah-Mohammadi, Andres Kwasinski
Two key challenges in underlay dynamic spectrum access (DSA) are how to establish an interference limit from the primary network (PN) and how cognitive radios (CRs) in the secondar…
Learning for Robust Routing Based on Stochastic Game in Cognitive Radio Networks
Wenbo Wang, Andres Kwasinski, Dusit Niyato +1
This paper studies the problem of robust spectrum-aware routing in a multi-hop, multi-channel Cognitive Radio Network (CRN) with the presence of malicious nodes in the secondary ne…
A Survey on Applications of Model-Free Strategy Learning in Cognitive Wireless Networks
Wenbo Wang, Andres Kwasinski, Dusit Niyato +1
Model-free learning has been considered as an efficient tool for designing control mechanisms when the model of the system environment or the interaction between the decision-makin…
Power allocation with stackelberg game in femtocell networks: a self-learning approach
Wenbo Wang, Andres Kwasinski, Zhu Han
This paper investigates the energy-efficient power allocation for a two-tier, underlaid femtocell network. The behaviors of the Macrocell Base Station (MBS) and the Femtocell Users…