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dc.contributor.authorTeo, Willy Way Yangen_US
dc.identifier.citationTeo, W. W. Y. (2022). Deep learning based channel estimation for OFDM system. Final Year Project (FYP), Nanyang Technological University, Singapore.
dc.description.abstractIn this project, we aim to study and design a deep learning based receiver for orthogonal frequency-division multiplexing (OFDM) system. OFDM has been widely adopted in wireless broadband communications to combat frequency-selective fading in wireless channels. In this project, we take advantage of deep learning in handling wireless OFDM channels in an end-to-end approach. We will explore the advantage of the deep learning model to recover the distorted signal. Moreover, the channel state information will not be required as compared with the traditional method. MATLAB simulation will be studied in this project to generate the dataset, and Python programming will be used to train the deep learning neural network.en_US
dc.publisherNanyang Technological Universityen_US
dc.subjectEngineering::Electrical and electronic engineeringen_US
dc.titleDeep learning based channel estimation for OFDM systemen_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.supervisorTeh Kah Chanen_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.degreeBachelor of Engineering (Electrical and Electronic Engineering)en_US
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Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)
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