Joint Blind Identification of the Number of Transmit Antennas and MIMO Schemes Using Gerschgorin Radii and FNN

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dc.contributor.VIAF113149196515374792028 (Al-Dhahir, N)
dc.contributor.authorGao, Mingjun
dc.contributor.authorLi, Yongzhao
dc.contributor.authorDobre, Octavia A.
dc.contributor.authorAl-Dhahir, Naofal
dc.contributor.utdAuthorAl-Dhahir, Naofal
dc.date.accessioned2020-04-28T15:44:34Z
dc.date.available2020-04-28T15:44:34Z
dc.date.issued2018-11-13
dc.descriptionThis work was supported in part by the National Natural Science Foundation of China under Grant 61771365, in part by the Natural Science Foundation of Shaanxi Province under Grant 2017JZ022, in part by the 111 Project under Grant B08038, in part by the National Key Research and Development Program of China under Grant 2016YFB1200202,
dc.descriptionDue to copyright restrictions and/or publisher's policy full text access from Treasures at UT Dallas is limited to current UTD affiliates (use the provided Link to Article).
dc.description.abstractBlind enumeration of the number of transmit antennas and blind identification of multiple-input multiple-output (MIMO) schemes are two pivotal steps in MIMO signal identification for both military and commercial applications. Conventional approaches treat them as two independent problems, namely the source number enumeration and the presence detection of space-time redundancy. In this paper, we develop a joint blind identification algorithm to determine the number of transmit antennas and MIMO schemes simultaneously. By restructuring the received signals, we derive three subspace-rank features based on the signal subspace-rank to determine the number of transmit antennas and identify space-time redundancy. Then, a Gerschgorin radii-based method and a feed-forward neural network are employed to calculate these three features, and a minimal weighted norm-1 distance metric is utilized for decision making. In particular, our approach can identify additional MIMO schemes, which most previous works have not considered, and is compatible with both single-carrier and orthogonal frequency division multiplexing (OFDM) systems. The simulation results verify the viability of our proposed approach for single-carrier and OFDM systems and demonstrate its favorable identification performance for a short observation period with acceptable complexity.
dc.description.departmentErik Jonsson School of Engineering and Computer Science
dc.identifier.bibliographicCitationGao, Mingjun, Yongzhao Li, Octavia A. Dobre, and Naofal Al-Dhahir. 2019. "Joint Blind Identification of the Number of Transmit Antennas and MIMO Schemes Using Gerschgorin Radii and FNN." IEEE Transactions On Wireless Communications 18(1): 373-387, doi: 10.1109/TWC.2018.2879941
dc.identifier.issn1536-1276
dc.identifier.issue1
dc.identifier.urihttp://dx.doi.org/10.1109/TWC.2018.2879941
dc.identifier.urihttps://hdl.handle.net/10735.1/8319
dc.identifier.volume18
dc.language.isoen
dc.publisherInstitute of Electrical Electronics Engineers Inc
dc.rights©2018 IEEE
dc.source.journalIEEE Transactions on Wireless Communications
dc.subjectOrthogonal frequency division multiplexing
dc.subjectMIMO systems
dc.subjectTransmitting antennas
dc.subjectAntennas (Electronics)
dc.subjectAntenna arrays
dc.subjectRedundancy (Engineering)
dc.subjectWireless communication systems
dc.subjectNeural networks (Computer science)
dc.subjectOrthogonal frequency division multiplexing
dc.subjectSignal detection
dc.titleJoint Blind Identification of the Number of Transmit Antennas and MIMO Schemes Using Gerschgorin Radii and FNN
dc.type.genrearticle

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