Superimposed training designs for spatially correlated MIMO-OFDM systems

Tran, NN; Tuan, HD; Nguyen, HH

Superimposed training designs for spatially correlated MIMO-OFDM systems

Tran, NN Tuan, HD

Nguyen, HH

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Publication Type:: Conference Proceeding
Citation:: GLOBECOM - IEEE Global Telecommunications Conference, 2008, pp. 3549 - 3554
Issue Date:: 2008-12-01

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Field	Value	Language
dc.contributor.author	Tran, NN	en_US
dc.contributor.author	Tuan, HD https://orcid.org/0000-0003-0292-6061	en_US
dc.contributor.author	Nguyen, HH	en_US
dc.date.issued	2008-12-01	en_US
dc.identifier.citation	GLOBECOM - IEEE Global Telecommunications Conference, 2008, pp. 3549 - 3554	en_US
dc.identifier.isbn	9781424423248	en_US
dc.identifier.uri	http://hdl.handle.net/10453/16531
dc.description.abstract	Optimal training design and channel estimation for spatially correlated multiple-input multiple-output systems with orthogonal frequency-division multiplexing (MIMO-OFDM) is still an open research topic of great interest. Only one asymptotic design for a special case of channel correlations was proposed in the literature. To fill this gap, this paper applies tractable semi- definite programming (SDP) to obtain the optimal superimposed training signals for the general case of channel correlations. To improve computational efficiency, an approximate design in closed-form is also proposed. This approximate design is formed by minimizing an upper bound of the channel estimation mean-square error. Since the superimposed training approach is taken, the derivation of an optimal non-redundancy precoder for data detection enhancement is also given. Analytical and simulation results demonstrate the excellent performance of the proposed designs and their superior performance compared to the previously proposed design. © 2008 IEEE.	en_US
dc.relation.ispartof	GLOBECOM - IEEE Global Telecommunications Conference	en_US
dc.relation.isbasedon	10.1109/GLOCOM.2008.ECP.682	en_US
dc.title	Superimposed training designs for spatially correlated MIMO-OFDM systems	en_US
dc.type	Conference Proceeding
utslib.for	0915 Interdisciplinary Engineering	en_US
dc.location.activity	New Orleans, USA	en_US
dc.location.activity	WOS:000247428700009
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
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

Optimal training design and channel estimation for spatially correlated multiple-input multiple-output systems with orthogonal frequency-division multiplexing (MIMO-OFDM) is still an open research topic of great interest. Only one asymptotic design for a special case of channel correlations was proposed in the literature. To fill this gap, this paper applies tractable semi- definite programming (SDP) to obtain the optimal superimposed training signals for the general case of channel correlations. To improve computational efficiency, an approximate design in closed-form is also proposed. This approximate design is formed by minimizing an upper bound of the channel estimation mean-square error. Since the superimposed training approach is taken, the derivation of an optimal non-redundancy precoder for data detection enhancement is also given. Analytical and simulation results demonstrate the excellent performance of the proposed designs and their superior performance compared to the previously proposed design. © 2008 IEEE.

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