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There is an increase in usage of smaller cells or femtocells to improve performance and coverage of next-generation heterogeneous wireless networks (HetNets). However, the interference caused by femtocells to neighboring cells is a limiting performance factor in dense HetNets. This interference is being managed via distributed resource allocation methods. However, as the density of the network increases so does the complexity of such resource allocation methods. Yet, unplanned deployment of femtocells requires an adaptable and self-organizing algorithm to make HetNets viable. As such, we propose to use a machine learning approach based on Q-learning to solve the resource allocation problemmore »
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Free, publicly-accessible full text available March 1, 2023
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Free, publicly-accessible full text available January 1, 2023
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A bstract A search is presented for new particles produced at the LHC in proton-proton collisions at $$ \sqrt{s} $$ s = 13 TeV, using events with energetic jets and large missing transverse momentum. The analysis is based on a data sample corresponding to an integrated luminosity of 101 fb − 1 , collected in 2017–2018 with the CMS detector. Machine learning techniques are used to define separate categories for events with narrow jets from initial-state radiation and events with large-radius jets consistent with a hadronic decay of a W or Z boson. A statistical combination is made with anmore »Free, publicly-accessible full text available November 1, 2022
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Free, publicly-accessible full text available September 1, 2022
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Free, publicly-accessible full text available September 1, 2022
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Free, publicly-accessible full text available August 1, 2022
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Free, publicly-accessible full text available August 1, 2022