DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kwon, Jinman | - |
dc.contributor.author | SEUNGHYUN, JEON | - |
dc.contributor.author | Jeon, Yo-Seb | - |
dc.contributor.author | Poor, H. Vincent | - |
dc.date.accessioned | 2024-02-21T07:20:53Z | - |
dc.date.available | 2024-02-21T07:20:53Z | - |
dc.date.created | 2024-02-20 | - |
dc.date.issued | 2024-06 | - |
dc.identifier.issn | 1536-1276 | - |
dc.identifier.uri | https://oasis.postech.ac.kr/handle/2014.oak/120324 | - |
dc.description.abstract | This paper considers a data detection problem in multiple-input multiple-output (MIMO) communication systems with hardware impairments. To address challenges posed by nonlinear and unknown distortion in received signals, two learning-based detection methods, referred to as model-driven and data-driven, are presented. The model-driven method employs a generalized Gaussian distortion model to approximate the conditional distribution of the distorted received signal. By using the outputs of coarse data detection as noisy training data, the model-driven method avoids the need for additional signaling overhead beyond traditional pilot overhead for channel estimation. An expectation-maximization algorithm is devised to accurately learn the parameters of the distortion model from noisy training data. To resolve a model mismatch problem in the model-driven method, the data-driven method employs a deep neural network (DNN) for approximating a-posteriori probabilities for each received signal. This method uses the outputs of the model-driven method as noisy labels and therefore does not require extra training overhead. To avoid the overfitting problem caused by noisy labels, a robust DNN training algorithm is devised, which involves a warm-up period, sample selection, and loss correction. Simulation results demonstrate that the two proposed methods outperform existing solutions with the same overhead under various hardware impairment scenarios. IEEE | - |
dc.language | English | - |
dc.publisher | Institute of Electrical and Electronics Engineers | - |
dc.relation.isPartOf | IEEE Transactions on Wireless Communications | - |
dc.title | MIMO Detection under Hardware Impairments: Learning with Noisy Labels | - |
dc.type | Article | - |
dc.identifier.doi | 10.1109/twc.2023.3329521 | - |
dc.type.rims | ART | - |
dc.identifier.bibliographicCitation | IEEE Transactions on Wireless Communications, v.23, no.6, pp.1 - 1 | - |
dc.identifier.wosid | 001247163400079 | - |
dc.citation.endPage | 1 | - |
dc.citation.number | 6 | - |
dc.citation.startPage | 1 | - |
dc.citation.title | IEEE Transactions on Wireless Communications | - |
dc.citation.volume | 23 | - |
dc.contributor.affiliatedAuthor | Kwon, Jinman | - |
dc.contributor.affiliatedAuthor | SEUNGHYUN, JEON | - |
dc.contributor.affiliatedAuthor | Jeon, Yo-Seb | - |
dc.identifier.scopusid | 2-s2.0-85177094659 | - |
dc.description.journalClass | 1 | - |
dc.description.journalClass | 1 | - |
dc.type.docType | Article | - |
dc.subject.keywordPlus | MASSIVE MIMO | - |
dc.subject.keywordPlus | DEEP | - |
dc.subject.keywordPlus | SYSTEMS | - |
dc.subject.keywordAuthor | Nonlinear distortion | - |
dc.subject.keywordAuthor | MIMO communication | - |
dc.subject.keywordAuthor | Hardware | - |
dc.subject.keywordAuthor | Radio frequency | - |
dc.subject.keywordAuthor | Training | - |
dc.subject.keywordAuthor | Noise measurement | - |
dc.subject.keywordAuthor | Receivers | - |
dc.subject.keywordAuthor | Multiple-input multiple-output (MIMO) detection | - |
dc.subject.keywordAuthor | hardware impairments | - |
dc.subject.keywordAuthor | model-driven approach | - |
dc.subject.keywordAuthor | data-driven approach | - |
dc.subject.keywordAuthor | learning with noisy labels | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.relation.journalWebOfScienceCategory | Telecommunications | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalResearchArea | Telecommunications | - |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.
library@postech.ac.kr Tel: 054-279-2548
Copyrights © by 2017 Pohang University of Science ad Technology All right reserved.