MIMO detection with high-level modulations using power equality constraints

Nevat, I; Yang, T; Avnit, K; Yuan, J

MIMO detection with high-level modulations using power equality constraints

Nevat, I Yang, T

Avnit, K Yuan, J

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Publication Type:: Journal Article
Citation:: IEEE Transactions on Vehicular Technology, 2010, 59 (7), pp. 3383 - 3392
Issue Date:: 2010-09-01

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Field	Value	Language
dc.contributor.author	Nevat, I	en_US
dc.contributor.author	Yang, T https://orcid.org/0000-0002-9870-6866	en_US
dc.contributor.author	Avnit, K	en_US
dc.contributor.author	Yuan, J	en_US
dc.date.issued	2010-09-01	en_US
dc.identifier.citation	IEEE Transactions on Vehicular Technology, 2010, 59 (7), pp. 3383 - 3392	en_US
dc.identifier.issn	0018-9545	en_US
dc.identifier.uri	http://hdl.handle.net/10453/39576
dc.description.abstract	This paper proposes computationally efficient algorithms for the detection of symbols of high-level modulation constellations in multiple-inputmultiple- output (MIMO) systems. The proposed approach is based on replacing the maximum-likelihood constraint with a finite set of power equality constraints (PECs), resulting in a set of nonconvex optimization problems, which can efficiently be solved using the hidden convexity methodology. Next, using specific structural properties of the proposed approach, we develop an ordered PEC algorithm, which provides a significant computational complexity reduction with no performance degradation. Based on that, an improved OPEC algorithm, which incorporates a heuristic local search, is proposed. Numerical results show that the proposed detectors significantly outperform the conventional minimum-mean-square-error (MMSE) detector in terms of bit error rate (BER) performance, with only a slightly higher complexity. © 2006 IEEE.	en_US
dc.relation.ispartof	IEEE Transactions on Vehicular Technology	en_US
dc.relation.isbasedon	10.1109/TVT.2010.2047957	en_US
dc.subject.classification	Automobile Design & Engineering	en_US
dc.title	MIMO detection with high-level modulations using power equality constraints	en_US
dc.type	Journal Article
utslib.citation.volume	7	en_US
utslib.citation.volume	59	en_US
utslib.for	08 Information and Computing Sciences	en_US
utslib.for	09 Engineering	en_US
utslib.for	10 Technology	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
utslib.copyright.status	closed_access
pubs.issue	7	en_US
pubs.publication-status	Published	en_US
pubs.volume	59	en_US

Abstract:

This paper proposes computationally efficient algorithms for the detection of symbols of high-level modulation constellations in multiple-inputmultiple- output (MIMO) systems. The proposed approach is based on replacing the maximum-likelihood constraint with a finite set of power equality constraints (PECs), resulting in a set of nonconvex optimization problems, which can efficiently be solved using the hidden convexity methodology. Next, using specific structural properties of the proposed approach, we develop an ordered PEC algorithm, which provides a significant computational complexity reduction with no performance degradation. Based on that, an improved OPEC algorithm, which incorporates a heuristic local search, is proposed. Numerical results show that the proposed detectors significantly outperform the conventional minimum-mean-square-error (MMSE) detector in terms of bit error rate (BER) performance, with only a slightly higher complexity. © 2006 IEEE.

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http://hdl.handle.net/10453/39576