2022
DOI: 10.1109/access.2022.3180753
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Optimal Resource Allocation for GAA Users in Spectrum Access System Using Q-Learning Algorithm

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Cited by 7 publications
(2 citation statements)
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“…Thompson sampling is used to find the state information efficiently by integrating reinforcement learning for all channels. Furthermore, we modeled the channel allocation problem as a multi-objective optimization problem in [44] and proposed the SAS-QLA algorithm in [45] based on reinforcement learning to assign the channels to the GAA users through a competitive auction process where the SAS acts as auctioneer. The field trials and the hardware experiments are investigated in [46], [47] without considering the collision scenarios of GAA-to-GAA users and GAA-to-PAL users.…”
Section: Related Workmentioning
confidence: 99%
“…Thompson sampling is used to find the state information efficiently by integrating reinforcement learning for all channels. Furthermore, we modeled the channel allocation problem as a multi-objective optimization problem in [44] and proposed the SAS-QLA algorithm in [45] based on reinforcement learning to assign the channels to the GAA users through a competitive auction process where the SAS acts as auctioneer. The field trials and the hardware experiments are investigated in [46], [47] without considering the collision scenarios of GAA-to-GAA users and GAA-to-PAL users.…”
Section: Related Workmentioning
confidence: 99%
“…Gao et al evaluate all three approaches using a suite of propagation models and GIS map data of Virginia Beach and San Diego [2], [3], showing that all three approaches are indeed effective at reducing potential interference. In contrast to WINNFORM, Abbass et al explore the application of Q-learning for spectrum allocation in CBRS [16]. Specifically, the authors investigate opening up idle access priority access license (PAL) channels to general authorized access (GAA) users.…”
Section: A Citizens Broadband Radio Servicementioning
confidence: 99%