A convolution neural network based QPSK and 16QAM modulations simulator for a multiuser MIMO-OFDM transmission simulation over a Nakagami-m Fading channel

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bracu.type.groupResearch Publications
datacite.rightsMetadata Only
dc.contributor.authorAhmed, Mashrukh
dc.contributor.authorRabiul Alam, Md. Golam
dc.contributor.departmentDepartment of Computer Science and Engineering
dc.date.accessioned2026-08-19T06:09:50Z
dc.date.available2026-08-19T06:09:50Z
dc.date.issued2023-01-01
dc.description.abstractWireless communication has been a widespread method of data transfer in the modern era. Various modulation techniques have been found and among them 16QAM has proven to be the most efficient. This study provides a Convolutional Neural Network (CNN) approach for simulating 16QAM and QPSK modulation schemes over a multiuser MIMO-OFDM using the Keras library over Nakagami-m fading. It then examines the two modulation schemes to determine if QPSK might be a viable alternative to 16QAM. In this paper two analysis have been done, a realistic MIMO OFDM system simulation and weighted belief propagation decoding.
dc.description.versionPublished
dc.format.extent6 pages
dc.identifier.citationM. Ahmed and M. G. Rabiul Alam, "A Convolution Neural Network based QPSK and 16QAM Modulations Simulator for a Multiuser MIMO-OFDM Transmission Simulation over a Nakagami-m Fading Channel," 2023 5th International Conference on Sustainable Technologies for Industry 5.0 (STI), Dhaka, Bangladesh, 2023, pp. 1-6, doi: 10.1109/STI59863.2023.10465002.
dc.identifier.doi10.1109/STI59863.2023.10465002
dc.identifier.issn9798350394290
dc.identifier.other2-s2.0-85190287680
dc.identifier.urihttps://hdl.handle.net/10361/29311
dc.language.isoen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.hasversion10.1109/STI59863.2023.10465002
dc.relation.ispartof2023 5th International Conference on Sustainable Technologies for Industry 5 0 Sti 2023
dc.relation.ispartofseries2023 5th International Conference on Sustainable Technologies for Industry 5 0 Sti 2023
dc.relation.urihttps://ieeexplore.ieee.org/document/10465002
dc.rightsfalse
dc.subject16QAM
dc.subjectCNN
dc.subjectKeras
dc.subjectMIMO
dc.subjectNakagami-m fading
dc.subjectOFDM
dc.subjectQPSK
dc.subject.lcshWireless communication systems.
dc.subject.lcshComputer communication systems.
dc.titleA convolution neural network based QPSK and 16QAM modulations simulator for a multiuser MIMO-OFDM transmission simulation over a Nakagami-m Fading channel
dc.typeConference Proceeding
person.affiliation.nameBRAC University
person.affiliation.nameBRAC University
person.identifier.scopus-author-id59037406900
person.identifier.scopus-author-id57289396600

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