Search-free precoder selection for 5G new radio using neural networks

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buir.contributor.authorAkyıldız, Talha
buir.contributor.authorDuman, Tolga M.
dc.contributor.authorAkyıldız, Talha
dc.contributor.authorDuman, Tolga M.
dc.date.accessioned2021-02-04T11:02:02Z
dc.date.available2021-02-04T11:02:02Z
dc.date.issued2020-12
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.descriptionDate of Conference: 26-29 May 2020en_US
dc.descriptionConference name: 2020 IEEE International Black Sea Conference on Communications and Networking, BlackSeaCom 2020en_US
dc.description.abstractWe propose a search-free precoder selection method with neural networks motivated by the fact that large codebook sizes are adopted in 5G New Radio (5G-NR). The proposed method does not require an explicit codebook search unlike the traditional selection algorithms. Instead, it aims at finding the precoder matrix index that maximizes the corresponding channel capacity using a neural network directly. The network is trained off-line using extensive simulated data with the underlying channel statistics; however, the actual selection algorithm is based on simple calculations with the neural network, hence it is feasible for real time implementation. We demonstrate that the proposed search-free selection algorithm is highly efficient, i.e., it results in a performance very close to optimal precoder in the codebook while its complexity is significantly lower. Simulations with realistic channel models of 5G-NR corroborate these observations as well. We also show that pruning of the trained neural network gives a way to achieve further complexity reduction with a very small reduction in the system performance.en_US
dc.description.provenanceSubmitted by Evrim Ergin (eergin@bilkent.edu.tr) on 2021-02-04T11:02:02Z No. of bitstreams: 1 Search-free_precoder_selection_for_5G_new_radio_using_neural_networks.pdf: 1182014 bytes, checksum: 42da852b73b9e0ac9b640e0e5facecc3 (MD5)en
dc.description.provenanceMade available in DSpace on 2021-02-04T11:02:02Z (GMT). No. of bitstreams: 1 Search-free_precoder_selection_for_5G_new_radio_using_neural_networks.pdf: 1182014 bytes, checksum: 42da852b73b9e0ac9b640e0e5facecc3 (MD5) Previous issue date: 2020-12en
dc.identifier.doi10.1109/BlackSeaCom48709.2020.9234966en_US
dc.identifier.isbn9781728171272
dc.identifier.urihttp://hdl.handle.net/11693/54996
dc.language.isoEnglishen_US
dc.publisherIEEEen_US
dc.relation.isversionofhttps://doi.org/10.1109/BlackSeaCom48709.2020.9234966en_US
dc.source.title2020 IEEE International Black Sea Conference on Communications and Networking, BlackSeaCom 2020en_US
dc.subject5G New radioen_US
dc.subjectMIMOen_US
dc.subjectChannel state informationen_US
dc.subjectPrecodingen_US
dc.subjectNeural networksen_US
dc.titleSearch-free precoder selection for 5G new radio using neural networksen_US
dc.typeConference Paperen_US

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