Gridless Channel Estimation for mmWave Hybrid Massive MIMO Systems with Low-Resolution ADCs

Cited 0 time in webofscience Cited 0 time in scopus
  • Hit : 77
  • Download : 0
DC FieldValueLanguage
dc.contributor.authorKim, In Sooko
dc.contributor.authorChoi, Junilko
dc.date.accessioned2021-11-05T06:41:30Z-
dc.date.available2021-11-05T06:41:30Z-
dc.date.created2021-10-26-
dc.date.issued2021-07-
dc.identifier.citation21st IEEE Statistical Signal Processing Workshop, SSP 2021, pp.351 - 355-
dc.identifier.issn2373-0803-
dc.identifier.urihttp://hdl.handle.net/10203/288883-
dc.description.abstractThis paper proposes the Newtonized fully corrective forward greedy selection-cross validation-based (NFCFGS-CV-based) channel estimator for millimeter (mmWave) hybrid massive multiple-input multiple-output (MIMO) systems with low-resolution analog-to-digital converters (ADCs). The proposed NFCFGS algorithm is a gridless compressed sensing (CS) technique that combines the FCFGS and Newtonized orthogonal matching pursuit (NOMP) algorithms. In particular, NFCFGS performs single path estimation over the continuum at each iteration based on the previously estimated paths. The CV technique is adopted as an indicator of termination in the absence of the prior knowledge on the number of paths, which is a model validation technique that prevents overfitting. © 2021 IEEE.-
dc.languageEnglish-
dc.publisherIEEE Computer Society-
dc.titleGridless Channel Estimation for mmWave Hybrid Massive MIMO Systems with Low-Resolution ADCs-
dc.typeConference-
dc.identifier.scopusid2-s2.0-85113475309-
dc.type.rimsCONF-
dc.citation.beginningpage351-
dc.citation.endingpage355-
dc.citation.publicationname21st IEEE Statistical Signal Processing Workshop, SSP 2021-
dc.identifier.conferencecountryBL-
dc.identifier.doi10.1109/SSP49050.2021.9513836-
dc.contributor.localauthorChoi, Junil-
Appears in Collection
EE-Conference Papers(학술회의논문)
Files in This Item
There are no files associated with this item.

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0