Subspace-based self-interference cancellation for full-duplex MIMO transceivers
This paper addresses the self-interference (SI) cancellation at baseband for full-duplex MIMO communication systems in consideration of practical transmitter imperfections. In particular, we develop a subspace-based algorithm to jointly estimate the SI and intended channels and the nonlinear distort...
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| Published in | EURASIP journal on wireless communications and networking Vol. 2017; no. 1; pp. 55 - 14 |
|---|---|
| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
Cham
Springer International Publishing
23.03.2017
Springer Nature B.V |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1687-1499 1687-1472 1687-1499 |
| DOI | 10.1186/s13638-017-0839-x |
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| Abstract | This paper addresses the self-interference (SI) cancellation at baseband for full-duplex MIMO communication systems in consideration of practical transmitter imperfections. In particular, we develop a subspace-based algorithm to jointly estimate the SI and intended channels and the nonlinear distortions. By exploiting the covariance and pseudo-covariance of the received signal, we can increase the dimension of the received signal subspace while keeping the dimension of the signal subspace constant, and hence, the proposed algorithm can be applied to most of full-duplex MIMO configurations with arbitrary numbers of transmit and receive antennas. The channel coefficients are estimated, up to an ambiguity term, without any knowledge of the intended signal. A joint detection and ambiguity identification scheme is proposed. Simulation results show that the proposed algorithm can properly estimate the channel with only one pilot symbol and offers superior SI cancellation performance. |
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| AbstractList | This paper addresses the self-interference (SI) cancellation at baseband for full-duplex MIMO communication systems in consideration of practical transmitter imperfections. In particular, we develop a subspace-based algorithm to jointly estimate the SI and intended channels and the nonlinear distortions. By exploiting the covariance and pseudo-covariance of the received signal, we can increase the dimension of the received signal subspace while keeping the dimension of the signal subspace constant, and hence, the proposed algorithm can be applied to most of full-duplex MIMO configurations with arbitrary numbers of transmit and receive antennas. The channel coefficients are estimated, up to an ambiguity term, without any knowledge of the intended signal. A joint detection and ambiguity identification scheme is proposed. Simulation results show that the proposed algorithm can properly estimate the channel with only one pilot symbol and offers superior SI cancellation performance. This paper addresses the self-interference (SI) cancellation at baseband for full-duplex MIMO communication systems in consideration of practical transmitter imperfections. In particular, we develop a subspace-based algorithm to jointly estimate the SI and intended channels and the nonlinear distortions. By exploiting the covariance and pseudo-covariance of the received signal, we can increase the dimension of the received signal subspace while keeping the dimension of the signal subspace constant, and hence, the proposed algorithm can be applied to most of full-duplex MIMO configurations with arbitrary numbers of transmit and receive antennas. The channel coefficients are estimated, up to an ambiguity term, without any knowledge of the intended signal. A joint detection and ambiguity identification scheme is proposed. Simulation results show that the proposed algorithm can properly estimate the channel with only one pilot symbol and offers superior SI cancellation performance.This paper addresses the self-interference (SI) cancellation at baseband for full-duplex MIMO communication systems in consideration of practical transmitter imperfections. In particular, we develop a subspace-based algorithm to jointly estimate the SI and intended channels and the nonlinear distortions. By exploiting the covariance and pseudo-covariance of the received signal, we can increase the dimension of the received signal subspace while keeping the dimension of the signal subspace constant, and hence, the proposed algorithm can be applied to most of full-duplex MIMO configurations with arbitrary numbers of transmit and receive antennas. The channel coefficients are estimated, up to an ambiguity term, without any knowledge of the intended signal. A joint detection and ambiguity identification scheme is proposed. Simulation results show that the proposed algorithm can properly estimate the channel with only one pilot symbol and offers superior SI cancellation performance. |
| ArticleNumber | 55 |
| Author | Le-Ngoc, Tho Masmoudi, Ahmed |
| Author_xml | – sequence: 1 givenname: Ahmed surname: Masmoudi fullname: Masmoudi, Ahmed email: ahmed.masmoudi@mail.mcgill.ca organization: Department of Electrical and Computer Engineering, McGill University – sequence: 2 givenname: Tho surname: Le-Ngoc fullname: Le-Ngoc, Tho organization: Department of Electrical and Computer Engineering, McGill University |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/32226444$$D View this record in MEDLINE/PubMed |
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| Cites_doi | 10.1109/TSP.2012.2192925 10.1109/TVT.2013.2284712 10.1109/TSP.2003.822359 10.1109/TWC.2006.1633369 10.1109/JSAC.2014.2330093 10.1109/LSP.2012.2221710 10.1109/TCOMM.2003.816992 10.1109/JSAC.2008.080214 10.1109/TSP.2004.823504 10.1109/TSP.2004.826183 10.1109/78.348133 10.1109/TVT.2015.2461006 10.1109/TVT.2009.2039008 10.1109/18.243446 10.1109/TWC.2012.102612.111278 10.1109/GLOCOM.2009.5425817 10.1109/TVT.2016.2540538 |
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| Keywords | Subspace method parameter estimation MIMO SI suppression Second-order statistics Full-duplex communication |
| Language | English |
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| SubjectTerms | Algorithms Ambiguity Applications Cancellation Channels Communication systems Communications Engineering Design Engineering Estimates Full-Duplex Radio: Theory Information Systems Applications (incl.Internet) Networks Signal,Image and Speech Processing Subspaces Symbols |
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| Title | Subspace-based self-interference cancellation for full-duplex MIMO transceivers |
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